Electronic and imaging systems for measuring particulate matter, and methods for measuring particulate matter.

Abstract

An electronic system, an imaging system, and a method for measuring particulate matter are provided. The electronic system includes an illuminator, a sensor, and a processor. The illuminator outputs light. The sensor includes a pixel array that generates an analog signal based on the scattered light from the output light, and a conversion circuit that converts the analog signal into digital signals corresponding to the gain values. The processor counts the number of values ​​in the digital signals that are greater than or equal to a threshold, and calculates the concentration of particulate matter within a target size range based on the change in the counted number according to the change in the gain value.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to Korean Patent Application No. 10-2019-0129958, filed on October 18, 2019, the entire disclosure of which is incorporated herein by reference. Technical Field

[0003] Embodiments of the present invention relate to semiconductor devices and systems including optical sensors, and more specifically, to electronic systems and imaging systems for measuring particulate matter, and methods for measuring particulate matter. Background Technology

[0004] Light sensors are used in a variety of electronic devices, including smartphones. They can be used to capture external images by converting external light into electrical signals. Light sensors can be implemented to perform various functions, such as using the sensed image to calculate the distance to an object, identify objects, and capture and display external images simply.

[0005] Due to advancements in industrial technology, significant progress has been made in the combustion of fossil fuels and in gas emissions from factories, automobiles, and other sources. As a result, particulate matter (PM) is generated and floats in the atmosphere. Such particulate matter can adversely affect the respiratory system, eyes, skin, and other systems. Therefore, interest in particulate matter is increasing, as is the desire to understand its current concentration. Furthermore, there is a need for solutions that allow individuals to measure particulate matter using the aforementioned optical sensors. Summary of the Invention

[0006] One or more exemplary embodiments provide electronic and imaging systems for measuring particulate matter concentration for each of a variety of sizes, and methods for measuring particulate matter.

[0007] According to one aspect of an exemplary embodiment, an electronic system is provided, comprising: an illuminator configured to output light; a sensor including a pixel array and a conversion circuit, the pixel array being configured to generate an analog signal based on scattered light from the output light, the conversion circuit being configured to convert the analog signal into digital signals corresponding to the gain values ​​respectively; and a processor configured to determine the number of values ​​of the digital signals that are greater than or equal to a threshold, and to determine the concentration of particulate matter having a target size range based on the change in the determined number of values ​​according to the change in the gain values.

[0008] According to another exemplary embodiment, an image system is provided, comprising: a pixel array including a first pixel and a second pixel, the first pixel being configured to generate a first analog signal based on scattered light corresponding to light of a first wavelength band output from a light source, and the second pixel being configured to generate a second analog signal based on light of a second wavelength band smaller than the first wavelength band; a conversion circuit configured to convert the first analog signal into a first digital signal corresponding to a gain value, and to convert the second analog signal into a second digital signal; and a processor configured to determine the concentration of particulate matter in a region where the output light is located based on the number of values ​​of each of the first digital signals that are greater than or equal to a threshold and the variation of the number.

[0009] According to another exemplary embodiment, a method for measuring particulate matter is provided, the method comprising: generating an analog signal by sensing scattered light from an output of light; converting the analog signal into digital signals corresponding to the gain values ​​respectively; determining the number of values ​​of the digital signals that are greater than or equal to a threshold; and determining the concentration of particulate matter corresponding to at least one target size range based on the determined number.

[0010] According to another exemplary embodiment, an electronic device is provided, including a memory storing instructions and at least one processor configured to execute instructions to: determine a number of values ​​of digital signals corresponding to gain values ​​used to convert analog signals into digital signals that are greater than or equal to a threshold, the analog signals corresponding to scattered light incident on a pixel array; and determine a concentration of particles having a predetermined size range based on a change in the determined number according to a change in the gain value. Attached Figure Description

[0011] The above and other objects and features will become apparent from the detailed description of exemplary embodiments with reference to the accompanying drawings, in which:

[0012] Figure 1 This is a block diagram illustrating an electronic system or imaging system according to an exemplary embodiment;

[0013] Figure 2 This is a diagram illustrating a pixel array according to an exemplary embodiment;

[0014] Figure 3 This is a circuit diagram illustrating a pixel according to an exemplary embodiment;

[0015] Figure 4 This is a diagram illustrating a pixel array according to an exemplary embodiment;

[0016] Figure 5 This is a cross-sectional view showing a pixel array according to an exemplary embodiment;

[0017] Figure 6 It is a description Figure 5 The curve of the filter;

[0018] Figure 7 This is a block diagram illustrating a conversion circuit according to an exemplary embodiment;

[0019] Figure 8 It is a description Figure 7 The diagram depicts the analog signal and gain values.

[0020] Figure 9 This is a block diagram illustrating a processor according to an exemplary embodiment;

[0021] Figure 10 It is a description Figure 9 A diagram illustrating the operation of the counter;

[0022] Figure 11 It is a description Figure 9 A diagram illustrating the operation of the subtractor;

[0023] Figure 12 It is a description Figure 9 A diagram illustrating the operation of a particulate matter calculator;

[0024] Figure 13 This is a flowchart describing a method of operating a system according to an exemplary embodiment;

[0025] Figure 14 This is a flowchart describing a method of operating a system according to an exemplary embodiment;

[0026] Figure 15 This is a diagram illustrating an electronic device for its application system according to an exemplary embodiment;

[0027] Figure 16 This is a diagram illustrating an electronic device for its application system according to an exemplary embodiment; and

[0028] Figure 17 This is a block diagram of an image system according to an exemplary embodiment. Detailed Implementation

[0029] In the following, exemplary embodiments of the inventive concept(s) will be described clearly and in detail so that those skilled in the art can readily implement the inventive concept(s).

[0030] It should be understood that, as used herein, expressions such as “at least one of” modify the entire column of elements when following a column of elements, without modifying any individual elements within that column. For example, the expressions “at least one of [A], [B], and [C]” or “at least one of [A], [B], or [C]” mean only A, only B, only C, A and B, B and C, A and C, or A, B, and C.

[0031] Figure 1 This is a block diagram illustrating an electronic system or imaging system 100 according to an exemplary embodiment. (Refer to...) Figure 1 The electronic system or imaging system (hereinafter, System 100) includes an illuminator 110, a sensor 120, and a processor 130 (e.g., at least one processor). System 100 can measure particulate matter. System 100 can be implemented in various electronic devices, such as digital cameras, smartphones, tablet PCs, wearable devices, etc. System 100 can be implemented as an integrated circuit (IC) or a system-on-a-chip (SoC). However, it is to be understood that one or more other exemplary embodiments are not limited thereto, and System 100 can be implemented as any device or circuit for measuring particulate matter. For example, System 100 can be implemented as a dedicated electronic device for measuring particulate matter.

[0032] Illuminator 110 is configured to output light to the outside. Illuminator 110 may output light in a wavelength band (such as the infrared band) that is not sensed by the user. However, it is to be understood that one or more other exemplary embodiments are not limited thereto, and illuminator 110 may output light in a wavelength band different from the infrared band to the outside. Illuminator 110 may include a light source controller 111 and a light source 112.

[0033] The light source controller 111 can control the operation of the light source 112. The light source controller 111 can control the timing of the light output from the illuminator 110. For example, the light source controller 111 can control the output timing of the light based on a clock that switches during the output light time. Such a clock can be generated from or based on the sensor 120 or the processor 130.

[0034] The light source 112 can output light to the outside under the control of the light source controller 111. The light source 112 may include a light-emitting device that generates light based on electrical signals received from the light source controller 111. The light source 112 can output light in the infrared band, but is not limited to what is described above. The type of light source 112 is not limited; for example, the light source 112 can be implemented using a vertical-cavity surface-emitting laser (VCSEL).

[0035] Light emitted from light source 112 is scattered by particulate matter. Here, particulate matter can be defined as solid or liquid particles suspended in the air. Particulate matter can be classified according to its diameter. For example, the diameter of particulate matter defined by PM 10 can be 10 μm or smaller, and the diameter of fine particulate matter defined by PM 2.5 can be 2.5 μm or smaller. When light shines on particles with the same physical properties, the amount of scattered light is proportional to the mass concentration. That is, as the diameter of the particulate matter increases, the mass concentration of the particulate matter increases, and the amount of scattered light increases. By sensing the intensity of this scattered light, the concentration of particulate matter within a specific size range can be calculated or determined. Here, the specific size range can include various diameter ranges, including PM 10 and PM 2.5.

[0036] Sensor 120 senses light scattered by particulate matter. Sensor 120 can generate an analog signal as an electrical signal based on the scattered light and convert the analog signal into a digital signal. Sensor 120 may include a pixel array 121, a conversion circuit 122, a digital logic circuit 123, and a driving circuit 124.

[0037] Pixel array 121 includes a plurality of pixels PX arranged in a two-dimensional manner. Each of the plurality of pixels PX can generate an analog signal based on light received from the outside. Pixel array 121 can be controlled to generate analog signals by a drive signal provided from drive circuit 124. The analog signals can be provided to conversion circuit 122 through a plurality of column lines.

[0038] At least some of the multiple pixels PX can sense scattered light. When light source 112 outputs light in the infrared band, the scattered light can be light in the infrared band. At least some of the multiple pixels PX can generate analog signals based on the light in the infrared band. For example, when system 100 is a dedicated device for measuring particulate matter, all pixels PX included in pixel array 121 can sense light in the infrared band. As another example, when system 100 is a device for image capture (e.g., a digital camera or mobile phone), some of the multiple pixels PX can sense light in the infrared band, while other pixels can sense light in the visible light band. Details of pixel array 121 will be described later.

[0039] The conversion circuit 122 can convert an analog signal into a digital signal. The conversion circuit 122 can perform various operations for converting the analog signal into a digital signal in response to control signals from the drive circuit 124. In one example, the conversion circuit 122 can perform correlated double sampling (CDS) or pseudo-CDS to extract the valid signal components.

[0040] The conversion circuit 122 can convert analog signals into digital signals corresponding to various gain values. The conversion circuit 122 can also amplify analog signals based on the gain values. Information about the gain values ​​can be provided from the processor 130, and the drive circuit 124 can control the gain value of the conversion circuit 122 based on this information. To calculate the concentration based on the size range of particulate matter, the conversion circuit 122 can convert analog signals into digital signals while increasing the gain value.

[0041] For example, when converted using a first gain value (e.g., based on conversion using a first gain value), the analog signal caused by light scattered from PM 10 can be greater than or equal to a threshold. In this case, when converted using a second gain value greater than the first gain value (e.g., based on conversion using a second gain value greater than the first gain value), the analog signal caused by light scattered from PM 2.5 can be greater than or equal to a threshold. Here, the threshold can be defined as the level at which a particular pixel can be considered saturated. In this way, particulate matter and fine particulate matter can be distinguished, and the concentration based on the size range of the particulate matter can be calculated. Details of the conversion circuit 122 are described below.

[0042] Digital logic circuit 123 can temporarily store digital signals and output the stored digital signals to processor 130. Under the control of driver circuit 124, digital logic circuit 123 can sequentially latch digital signals and output the latched digital signals.

[0043] The driving circuit 124 can control the pixel array 121, the conversion circuit 122, and the digital logic circuit 123. For example, the driving circuit 124 can generate clock signals and timing control signals for the operation of the pixel array 121, the conversion circuit 122, and the digital logic circuit 123. The clock signals can be provided to the light source controller 111. In one example, the driving circuit 124 may include at least one of a logic control circuit, a phase-locked loop (PLL) circuit, a timing control circuit, a communication interface circuit, etc.

[0044] The driving circuit 124 can select one or more rows from a plurality of rows in the pixel array 121. Analog signals generated from pixels PX of the selected rows can be transmitted to the conversion circuit 122. The driving circuit 124 can control the pixel array 121 to repeatedly sense scattered light. The driving circuit 124 can control the pixel array 121 to generate an image signal corresponding to each gain value. Here, the image signal is included in the analog signal.

[0045] The driving circuit 124 can control the pixel array 121 to generate multiple frame signals at one (e.g., each) gain value. Here, the frame signals are included in the image signal. That is, the pixel array 121 can generate multiple frame signals for each gain value and output the multiple frame signals to the conversion circuit 122. The multiple frame signals can be digitally converted and averaged or combined by the conversion circuit 122 or the digital logic circuit 123. This is to improve the accuracy of particulate matter concentration calculation. However, it should be understood that one or more other exemplary embodiments are not limited to this, and averaging or combining can be performed by the processor 130.

[0046] The processor 130 can perform control operations for the control system 100 and computational operations for calculating various data. The processor 130 can control the light output of the illuminator 110. The processor 130 can allow or control the sensor 120 to generate digital signals by sensing scattered light.

[0047] Processor 130 can calculate or determine the concentration of particulate matter based on a range of particulate matter sizes, using digital signals. The digital signals may include values ​​corresponding to each of a plurality of pixels PX. Processor 130 can count the number of these values ​​that exceed a threshold. Pixels corresponding to values ​​greater than or equal to the threshold can be considered saturated by scattered light. In this case, the count value can be understood as the number of saturated pixels at a specific gain value. Processor 130 can receive digital signals corresponding to gain values ​​respectively and count the number of values ​​greater than or equal to the threshold for each digital signal. When the number of gain values ​​is sixteen, sixteen count values ​​can be generated.

[0048] Processor 130 can calculate the changes in count values ​​corresponding to the gain values, respectively. Here, the change can be understood as the change in the number of saturated pixels relative to the gain value, and can be represented as a difference value. For example, when the gain values ​​are 1 to 16, first to sixteenth count values ​​corresponding to gain values ​​1 to 16 can be calculated or determined, respectively. Processor 130 can calculate the difference value corresponding to the second gain value by subtracting the first count value from the second count value. Processor 130 can calculate the difference value corresponding to the third gain value by subtracting the second count value from the third count value. This difference value or change can indicate the intensity or quantity of scattered light within a specific range. Therefore, this difference value or change can be related to the size of the scattered light particles.

[0049] Processor 130 can generate (or determine or obtain) particulate matter data corresponding to a specific size range by applying a correction factor to the calculated difference value. The correction factor can be determined based on the size range of the particulate matter to be calculated. Multiple particulate matter size ranges can be provided, such as PM 2.5 and PM 10. For example, particulate matter data can include particulate matter data corresponding to PM 2.5 and particulate matter data corresponding to PM 10. The correction factor can be based on a unit volume (e.g., 1 m³). 3 This can be used to convert particulate matter data, and the particulate matter data can be used to calculate particulate matter concentration for each size range.

[0050] Unlike the above description, at least a portion of the counting operation, change calculation operation, and correction factor calculation operation performed by the processor 130 can be executed by the digital logic circuit 123. In this case, the digital logic circuit 123 can count values ​​greater than or equal to a threshold in the digital signal generated by the conversion circuit 122.

[0051] Processor 130 can determine the operating mode of system 100. For example, pixel array 121 may include a first pixel sensing the infrared band and a second pixel sensing the visible light band. In an operating mode for measuring particulate matter, processor 130 may activate illuminator 110 and control sensor 120 such that the first pixel senses scattered light (i.e., to detect or measure particulate matter). In an operating mode for normal image capture, processor 130 may deactivate illuminator 110 and control sensor 120 such that the second pixel senses light in the visible light band (i.e., to capture an image).

[0052] Figure 2 This is a diagram illustrating a pixel array 121_1 according to an exemplary embodiment. Figure 2 The pixel array 121_1 shown can correspond to Figure 1 The pixel array is 121. (Refer to...) Figure 2 The pixel array 121_1 includes multiple pixels PX1 to PX9. The multiple pixels PX1 to PX9 are arranged in a two-dimensional manner.

[0053] exist Figure 2 In an exemplary embodiment, all pixels PX1 to PX9 can be determined according to... Figure 1 The illuminator 110 outputs light to sense scattered light. That is, all pixels PX1 to PX9 can sense light, for example, in the infrared band. In this case, Figure 1 Includes Figure 2The system 100 with pixel array 121_1 can be implemented as a dedicated device for measuring particulate matter, although this is only an example and one or more other exemplary embodiments are not limited thereto. For example, the system 100 can be implemented to perform additional operations (such as depth measurement) beyond the operation for measuring particulate matter, which can be performed by sensing light in the infrared band.

[0054] Figure 3 This is a circuit diagram illustrating a pixel PX according to an exemplary embodiment. Pixel PX may correspond to... Figure 1 PX or Figure 2 One of the pixels PX1 to PX9. (Refer to...) Figure 3 A pixel PX can include a photoelectric conversion element PD, a reset transistor RX, a selection transistor SX, and a drive transistor DX. To understand this, Figure 3 The circuit structure is exemplary, and Figure 1 and Figure 2 The pixel structure is not limited to Figure 3 For example, a pixel PX may also include a transfer transistor connected between the photoelectric conversion element PD and the driving transistor DX. Additionally, a pixel PX may include a conversion gain transistor and a capacitor for configuring a variable conversion gain circuit.

[0055] A photoelectric conversion element (PD) generates and accumulates charge based on at least one of the amount and intensity of light incident upon it. When the photoelectric conversion element (PD) is included... Figure 2 When the pixel array 121_1 is included (or based on the photoelectric conversion element PD is included) Figure 2 In the pixel array 121_1, the photoelectric conversion element PD can generate and accumulate charge based on scattered light in the infrared band. For example, the photoelectric conversion element PD can be a photodiode that uses InGaAs (indium gallium arsenide) to sense light in the infrared band, but is not limited thereto in one or more other exemplary embodiments. For example, the photoelectric conversion element PD can be a photodiode, a phototransistor, a photogate, a pinned photodiode (PPD), or a combination thereof.

[0056] The charge generated from the photoelectric conversion element PD is transferred to the floating diffusion region FD. The pixel PX may also include a transfer transistor for controlling the charge transfer. The exposure time of the photoelectric conversion element PD can be controlled by the transfer transistor. For example, instead of amplifying an analog signal, based on... Figure 1 The gain value in the conversion circuit 122, and the drive circuit 124 can control the transmission transistor to perform... Figure 1 The gain value is adjusted in the circuit. Therefore, an exposure time dependent on the gain value can be provided, and the conversion circuit 122 can convert the analog signal generated based on the exposure time into a digital signal. In this case, as... Figure 1As shown, the conversion circuit 122 can change the gain value without generating a digital signal.

[0057] The floating diffusion region FD can accumulate charge transferred from the photoelectric conversion element PD. The driving transistor DX can be controlled based on the amount of charge accumulated in the floating diffusion region FD.

[0058] The reset transistor RX resets the charge accumulated in the floating diffusion region FD. The drain terminal of the reset transistor RX can be connected to the floating diffusion region FD, and the source terminal of the reset transistor RX can be connected to the pixel power supply voltage VPIX. The reset transistor RX can be turned on or off based on the reset signal RG. Figure 1 The drive circuit 124 provides a reset signal RG. When the reset transistor RX is turned on, the pixel power supply voltage VPIX can be transmitted to the floating diffusion region FD. In this case, the charge accumulated in the floating diffusion region FD can be released, and the floating diffusion region FD can be reset.

[0059] The driving transistor DX can be a source follower buffer amplifier that generates a source-drain current proportional to the amount of charge input to the gate electrode in the floating diffusion region FD. The driving transistor DX amplifies the potential change in the floating diffusion region FD and outputs the amplified signal to the column line CL by selecting the transistor SX.

[0060] The selection transistor SX is used to select the pixel PX to be read line by line. The selection transistor SX can be turned on or off based on the selection signal SEL. Figure 1 The drive circuit 124 provides a selection signal SEL. When the selection transistor SX is turned on by the selection signal SEL, the analog signal output from the drive transistor DX can be output to the column line CL.

[0061] Figure 4 This is a diagram illustrating a pixel array 121_2 according to an exemplary embodiment. Pixel array 121_2 may correspond to... Figure 1 The pixel array is 121. (Refer to...) Figure 4 The pixel array 121_2 includes a plurality of pixels. The plurality of pixels are arranged in two dimensions on a plane defined by a first direction DR1 and a second direction DR2.

[0062] exist Figure 4 In an exemplary embodiment, the pixel array 121_2 may include a first pixel that senses light in a first band (e.g., the infrared (IR) band) and a second pixel (a color pixel) that senses light in a second band (e.g., the visible light band). For example, the second pixel may include a red pixel corresponding to red, a green pixel corresponding to green, and a blue pixel corresponding to blue. In this case, Figure 1Includes Figure 4 The system 100 with pixel array 121_2 can selectively perform operations for measuring particulate matter and normal image capture operations.

[0063] The first pixel (IR pixel) can be determined from... Figure 1 The illuminator 110 outputs light to sense scattered light. The first pixel can generate an analog signal based on the scattered light. For example... Figure 1 As described above, analog signals can be used to measure particulate matter.

[0064] The second pixel (color pixel) can generate an analog signal by sensing light in the visible light band during normal image capture operations. Figure 1 The conversion circuit 122 can generate a digital image signal based on the analog signal. In this case, the image signal corresponding to the first pixel can be corrected by pixel correction operations or the like.

[0065] To minimize image degradation and lens flaring during normal image capture operations, the number of first pixels can be limited. For example, the number of first pixels can be less than the number of second pixels. In this exemplary embodiment, as... Figure 4 As shown, the first pixel can be arranged in a specific manner. For example, the first pixel can be arranged such that at least four second pixels are disposed between two first pixels. Relative to the first pixel located at the center of the illustrated pixel array 121_2, other first pixels can be configured to have at least four second pixels between them in the first direction DR1, the second direction DR2, the third direction DR3, and the fourth direction DR4.

[0066] Figure 5 This is a cross-sectional view showing a pixel array 121_2 according to an exemplary embodiment. Figure 5 The pixel array 121_2 can correspond to Figure 4 The pixel array 121_2. Figure 5 Three pixels of pixel array 121_2 are shown. (Refer to...) Figure 5 The pixel array 121_2 may include a first pixel region PXa, a second pixel region PXb, a third pixel region PXc, a first color filter CFa, a second color filter CFb, a transparent component TM, and a microlens ML.

[0067] The first pixel region PXa and the second pixel region PXb can generate charge based on light in the visible light band. For example, the first pixel region PXa and the second pixel region PXb can include photodiodes for generating charge, such as Si photodiodes.

[0068] A first color filter CFa is disposed on a first pixel region PXa. The first color filter CFa allows light of a first color (e.g., green) to pass through. A second color filter CFb is disposed on a second pixel region PXb. The second color filter CFb allows light of a second color (e.g., blue) to pass through, a color different from the first color filter CFa. As a result, the first pixel region PXa can generate a charge based on light corresponding to the first color, and the second pixel region PXb can generate a charge based on light corresponding to the second color.

[0069] The third pixel region PXc can generate charge based on light in the infrared band. For example, the third pixel region PXc may include a photodiode for generating charge. In this case, to sense light in the infrared band, the third pixel region PXc may include, for example, an InGaAs photodiode, although one or more other exemplary embodiments are not limited to what has been described above. To sense light in a wavelength band different from that of the first pixel region PXa and the second pixel region PXb, at least a portion of the material included in the third pixel region PXc may be different from the materials of the first pixel region PXa and the second pixel region PXb. Alternatively, to sense light in a different wavelength band, the doping concentration of at least a portion of the third pixel region PXc may be different from the doping concentration of the first pixel region PXa and the second pixel region PXb.

[0070] A transparent component TM can be disposed on the third pixel region PXc. Because the third pixel region PXc senses light in the infrared band, a separate color filter is not required on it. However, to compensate for height according to the arrangement of the first color filter CFa and the second color filter CFb, the transparent component TM can be disposed on the third pixel region PXc. The transparent component TM allows light in both the infrared and visible light bands to pass through.

[0071] Microlenses ML are disposed on the first color filter CFa, the second color filter CFb, and the transparent component TM. Microlenses ML can focus light entering the first to third pixel areas PXa, PXb, and PXc, thereby improving the light sensing effect.

[0072] A filter FI can be disposed on the pixel array 121_2. The filter FI allows light in a wavelength band that is being performed or needs to be sensed to pass through. Here, the wavelength band being performed or needs to be sensed may include at least a portion of the visible light band (e.g., the first wavelength band) to be sensed by the first pixel region PXa and the second pixel region PXb, and at least a portion of the infrared band (e.g., the second wavelength band) to be sensed by the third pixel region PXc. As an example, the filter FI can filter light in a third wavelength band between the first and second wavelength bands. The third wavelength band may be, for example, 700 nm to 1000 nm.

[0073] The lens unit LU can refract light incident on the pixel array 121_2 and transmit the light to the pixel array 121_2. Scattered light caused by particles or light in the visible light band used for image capture can pass through the lens unit LU and the filter FI and be transmitted to the pixel array 121_2.

[0074] Figure 6 It is a description Figure 5 The filter's curve. (Refer to...) Figure 6 The horizontal axis is defined as the wavelength of light, and the vertical axis is defined as the response intensity to light of a specific wavelength, i.e., spectral sensitivity. Figure 4 or Figure 5 The pixel array 121_2 may include red pixels, green pixels, blue pixels and infrared (IR) pixels.

[0075] Red, green, and blue pixels can have peak spectral sensitivity in the visible light band between 400 nm and 700 nm. Additionally, infrared pixels can have peak spectral sensitivity in the infrared band greater than 1000 nm. Figure 5 The filter FI allows light in the first wavelength band PA1, which corresponds to the visible light band less than 700 nm, and the second wavelength band PA2, which corresponds to the infrared band greater than 1000 nm, to pass through.

[0076] Figure 5 The filter FI can filter light in the wavelength band between 700nm and 1000nm. Red, green, blue, and infrared pixels exhibit uniform spectral sensitivity in the 700nm-1000nm wavelength band. When light is not blocked in the 700nm-1000nm wavelength band, light in this band is sensed from each pixel. In this case, the accuracy of image capture operations or particle measurement operations is reduced. That is, Figure 5 The filter FI allows light from the first wavelength band PA1 and the second wavelength band PA2 to pass through while blocking light from the wavelength band in between, thereby improving the reliability of image capture and particulate matter measurement operations.

[0077] Figure 7 This is a block diagram illustrating a conversion circuit 122 according to an exemplary embodiment. Figure 7 The conversion circuit 122 can correspond to Figure 1 The conversion circuit 122 is shown. (Refer to...) Figure 7 The conversion circuit 122 may include a correlated dual sampler (CDS) 122_1, a gain amplifier 122_2, and an analog-to-digital converter 122_3. For ease of explanation, Figure 7The structure of the conversion circuit 122 will be understood as an exemplary block diagram used to separately describe the function or operation of the conversion circuit. For example, the operations performed in the correlated double sampler (CDS) 122_1, the gain amplifier 122_2, and the analog-to-digital converter 122_3 can be implemented in an integrated circuit, and an integrated circuit can perform correlated double sampling, gain amplification, digital conversion, etc.

[0078] The conversion circuit 122 can receive an analog signal PS generated based on scattered light caused by particulate matter. The analog signal PS can be provided to a correlated double sampler 122_1. For example, the correlated double sampler (CDS) 122_1 can remove fixed-mode noise (FPN) from the analog signal PS. The correlated double sampler 122_1 can, for example, output an analog signal sampled based on the difference between the analog signal PS and a reference signal to a gain amplifier 122_2.

[0079] Gain amplifier 122_2 can amplify the sampled analog signal based on a gain value. For example, gain amplifier 122_2 can output the result of multiplying the sampled analog signal by a specified gain value. As described above, the gain value can be increased sequentially for particulate matter measurement. The gain value can increase sequentially from 1 to 16. When ten images (analog signals) for one gain value are generated from pixel array 121, the same gain value can be used to amplify these ten images. Subsequently, the gain value is increased by one, and the increased gain value can be used to amplify ten more images. The concentration based on the size of the particulate matter can be calculated using analog signals amplified with different gain values.

[0080] Analog-to-digital converter 122_3 can convert an analog signal amplified based on a gain value into a digital signal PD. Analog-to-digital converter 122_3 can sequentially convert multiple signals amplified based on successively increasing gain values ​​into digital signals. These digital signals PD correspond to different gain values. For example, the gain value can increase sequentially from 1 to 16, and ten signals (e.g., frame signals) can be generated from the pixel array 121 for a single gain value. In this case, analog-to-digital converter 122_3 can generate 160 digital signals. However, it should be understood that one or more other exemplary embodiments are not limited to this. For example, according to another exemplary embodiment, 10 frame signals are averaged or combined before conversion, and analog-to-digital converter 122_3 can generate 16 digital signals. A digital signal can have a digital value corresponding to each pixel. This value depends on the intensity of the scattered light received by each pixel.

[0081] Figure 8 It is a description Figure 7 The diagram depicts the analog signal and gain values. (Refer to...) Figure 8The horizontal axis is defined as time, and the vertical axis is defined as the magnitude of the analog signal PS, such as the voltage level of the analog signal. Figure 1 When each pixel PX in the pixel array 121 senses scattered light caused by particulate matter, an analog signal PS can be generated. Here, the analog signal PS can be understood as an analog signal corresponding to one pixel PX.

[0082] Particulate matter is suspended in the air and can move continuously over time. Therefore, the voltage level generated by pixel PX can change continuously over time. Taking this movement into account, pixel PX can sense the scattered light a certain number of times relative to a gain value. This number (the number of reference scans) is preset and can be, for example, ten times. In this case, the analog signal PS generated from the ten sensed samples, or the digital signal generated from the analog signal PS, can be averaged or combined. Therefore, the reliability of particulate matter concentration calculation can be improved.

[0083] As mentioned above, the level of the analog signal PS depends on the size of the scattered light particles. As the particle size increases, the amount or intensity of scattered light increases, and consequently, the level of the analog signal PS increases. Figure 8 In the image, large and small particles can be distinguished based on the size of the peaks. The number of pixels PX that generate the analog signal PS depends on the amount of particles. That is, as the amount of particles increases, the number of pixels PX that sense the scattered light increases.

[0084] Figure 1 The conversion circuit 122 or Figure 7 The gain amplifier 122_2 can amplify the analog signal PS while increasing the gain value. The amplified analog signal PS can be converted into a digital signal, and the number of values ​​greater than or equal to a threshold can be counted or determined in the digital signal (or based on the digital signal, corresponding to the digital signal, included in the digital signal, represented by the digital signal, etc.). The number of count values ​​depends on the number of pixels sensing scattered light exceeding a specified intensity. That is, the number of count values ​​can be related to or indicate the concentration of particles exceeding a specified size.

[0085] Even when the analog signal PS is amplified with a small gain value, the analog signal PS generated by large particles can still exceed the threshold. Conversely, when amplified with a large gain value, the analog signal PS generated by small particles can also exceed the threshold. Therefore, as the gain value increases, the change in the number of count values ​​can be related to the number or concentration of particles within a specified size range. Based on this concept, a system 100 according to an exemplary embodiment can calculate the size and amount (concentration) of particulate matter.

[0086] Figure 9This is a block diagram illustrating a processor 130 according to an exemplary embodiment. Figure 9 The processor 130 can correspond to Figure 1 The processor 130 is shown. (Refer to...) Figure 9 The processor 130 may include an average calculator 131, a counter 132, a subtractor 133, and a particulate matter (PM) calculator 134. For clarity, it is understood that, for ease of description... Figure 9 The structure of processor 130 is an exemplary block diagram for describing the overall operation of the particulate matter measurement function. At least one of the average calculator 131, counter 132, subtractor 133, and particulate matter calculator 134 can be in another configuration (e.g., Figure 1 The digital logic circuit 123) is executed.

[0087] The average calculator 131 can perform averaging or combining operations on digital signals PD. (See above for reference.) Figure 8 The above, Figure 1 The pixel array 121 can sense scattered light relative to a gain value using a reference scan number. Therefore, the analog signal used to measure particulate matter can include image signals corresponding to different gain values, and each image signal can include an analog frame signal generated by the reference scan number. The conversion circuit 122 can convert the analog frame signal generated by the reference scan number into a digital frame signal. The averaging calculator 131 can generate a digital image signal corresponding to a gain value by performing an averaging operation on the digital frame signal.

[0088] Although the foregoing has described how the average calculator 131 performs digital averaging or digital combining when included in the processor 130, it is to be understood that one or more other exemplary embodiments are not limited thereto. For example, the system 100 according to another exemplary embodiment may perform an averaging operation on an analog signal. In this case, the average calculator 131 may... Figure 1 The pixel array 121 and the conversion circuit 122 are configured, provided, or operated between them, or the pixel array 121 and the conversion circuit 122 may be included in the conversion circuit 122. Furthermore, as an example, an average calculator 131 may be included in the sensor 120 to calculate a digital average or perform digital merging. In this case, the average calculator 131 may be included in the conversion circuit 122 or the digital logic circuit 123.

[0089] Additionally, the average calculator 131 can perform an averaging operation on the count values ​​generated by the counter 132. In this case, the counter 132 can receive a digital signal PD, and the average calculator 131 can perform an averaging operation on the output of the counter 132.

[0090] Counter 132 can count the number of values ​​greater than or equal to a threshold in digital signals PD (e.g., averaged digital signals) corresponding to gain values. The digital signal PD (averaged digital signal) corresponding to a gain value can have values ​​corresponding to multiple pixels. Each value can be related to the result of multiplying the gain value by the intensity of the scattered light sensed by the corresponding pixel. As the number of scattered light particles increases, the number of count values ​​increases. Counter 132 can generate count values ​​corresponding to gain values. Details are described below. Figure 10 Describe it.

[0091] Subtractor 133 can calculate the change in a count value relative to a gain value. In one example, subtractor 133 can generate a subtraction value (difference or change) for a specific gain value by subtracting the count value for a previous gain value from the count value for a specific gain value. For example, when the specific gain value is 3, the previous gain value could be 2. The subtraction value can be related to the number of particles within a specific size range. Details are provided below. Figure 11 Describe it.

[0092] The particulate matter calculator 134 can generate (or determine) particulate matter data PMD based on a subtraction value. The particulate matter calculator 134 can generate values ​​relating to the amount of particulate matter in (multiple) target size ranges (e.g., PM 10 and PM 2.5). To this end, the particulate matter calculator 134 can apply a correction factor corresponding to the target size range to the subtraction value. For example, the particulate matter calculator 134 can multiply the subtraction value by a correction factor corresponding to PM 10. This correction factor can be different for each gain value. The corrected data value can relate to the amount or quantity of particulate matter within the target size range (e.g., a predetermined size range). The particulate matter calculator 134 is referenced below. Figure 12 Provide a detailed description.

[0093] The particulate matter calculator 134 can convert data corrected by a correction factor into a unit volume (e.g., 1 m³). 3 To generate particulate matter data (PMD). As light travels from... Figure 1 The output of the illuminator 110 has a scattering area whose volume differs from the unit volume. The particulate matter calculator 134 can multiply the corrected data by the ratio of the volume of that area to the unit volume. Therefore, the particulate matter calculator 134 can calculate the particulate matter concentration for each target size range.

[0094] Figure 10 It is a description Figure 9 A diagram illustrating the operation of counter 132. (Refer to...) Figure 10 The horizontal axis is defined as the gain value, and the vertical axis is defined as the count value. In this example, the gain values ​​are shown as 1 to 16.

[0095] As mentioned above, Figure 1 The sensor 120 can sense scattered light caused by particulate matter and then generate digital signals corresponding to different gain values. Each of these digital signals can have a value corresponding to a pixel that senses the scattered light. As the gain increases, the value can increase. Figure 9 The counter 132 can generate a count value by counting the number of values ​​greater than or equal to a threshold or by determining the number of values ​​greater than or equal to a threshold.

[0096] Reference Figure 10 As the gain value increases, the count value can also increase. This is because as the gain value increases, the amplification gain of the analog signal increases, thus increasing the numerical value. The count value depends on the number of pixels sensing the scattered light and is related to the number of particles. It will be understood that as the count value increases, the amount or number of sensed particles can increase.

[0097] Figure 11 It is a description Figure 9 A diagram illustrating the operation of subtractor 133. (Refer to...) Figure 11 The horizontal axis is defined as the gain value, and the vertical axis is defined as the subtraction value. For example, the gain values ​​are shown as 1 to 16.

[0098] As mentioned above, Figure 9 The subtractor 133 can generate a subtraction value for a specific gain value by subtracting a count value for a previous gain value from a count value for a specific gain value. For example, the first subtraction value can be... Figure 10 The first count value is the same. The second subtraction value can be obtained by comparing the count value with the count value obtained from the count value. Figure 10 The second count value minus the first count value yields the same value. That is, the subtraction can be understood as the change or difference between the count value and the gain value.

[0099] A large subtraction value indicates a large number of specific particles of a particular size. The subtraction value for a specific gain can be the number of pixels generating an analog signal at a specific range of voltage levels. This specific range of voltage levels can be a result of receiving scattered light due to particles within a specific size range. That is, the magnitude of the subtraction value can represent the number of particles within a specific size range. As the gain value increases, it is also possible to count pixels generating smaller voltage levels. Therefore, as the gain value corresponding to the subtraction value increases, it can represent the amount of particles within a smaller size range. Thus, the concentration of particles within a desired size range can be calculated.

[0100] Figure 12 It is a description Figure 9 A diagram illustrating the operation of the particulate matter calculator 123_4. (Refer to...) Figure 12 The horizontal axis is defined as the gain value, and the vertical axis is defined as the subtraction value.

[0101] As mentioned above, Figure 9 The particulate matter calculator 123_4 can calculate at least one of the number, amount, and concentration of particulate matter within a desired size range by applying a correction factor to the subtraction value. For example, a first particulate matter data PMa related to the number of particles with a diameter of 10 μm and a second particulate matter data PMb related to the number of particles with a diameter of 2.5 μm can be calculated. The first particulate matter data PMa can be generated by multiplying the first correction factor by the subtraction value, respectively. The second particulate matter data PMb can be generated by multiplying the second correction factor by the subtraction value, respectively. For example, each of the first and second correction factors can include different factor values ​​corresponding to the gain value, respectively.

[0102] Generally, the magnitude of the subtraction value depends on the number of particles within a specific size range. However, errors may occur in the relationship between the subtraction value and the number of particles within a specific size range, depending on the distance between the particles and pixels, the particle size, type, material, shape, and other factors of the system 100's adsorption capacity. Taking these various factors into account, a correction factor can be set to improve the reliability of particle concentration calculation. Furthermore, the particle calculator 123_4 can convert the first particle data (PMa) and the second particle data (PMb) into standard units of particle concentration.

[0103] Figure 13 This is a flowchart describing a method of operating a system 100 according to an exemplary embodiment. Figure 13 The operation can be performed in Figure 1 It is executed in system 100. Figure 13 The operation will be understood as the method of operation of system 100 for measuring particulate matter. For ease of description, reference will be made to... Figure 1 Description of reference numerals in the figures Figure 13 .

[0104] Reference Figure 13 In operation S110, the light source 112 can output infrared light. The output light can be scattered by particles. The scattered light can reach the pixel array 121 of the sensor 120 (or be incident on the pixel array 121 of the sensor 120).

[0105] In operation S120, system 100 can determine whether conditions for measuring particulate matter are met. For example, when the intensity of scattered or reflected light sensed in response to the output light is greater than a reference intensity, processor 130 can determine that an object exists in front of sensor 120. Here, the reference intensity can be understood as the intensity of the sensed light that makes the object determined to be adjacent to sensor 120. When particulate matter measurement is difficult due to this object, system 100 can notify the user of the presence of the object via an output device (e.g., a display or speaker). Operation S110 can then continue. When sensor 120 does not sense an object, operation S130 is executed.

[0106] In operation S130, sensor 120 can capture an image. Image capture here is understood as sensing scattered light. Because particles can move continuously over time, sensor 120 can generate an image by referencing the number of scans. The generated images can be merged into a single image through an averaging operation. Sensor 120 can convert the analog signal generated from pixel array 121 into a digital signal based on a set gain value. The image here can be a digital signal including values ​​corresponding to pixels PX respectively.

[0107] In operation S140, system 100 can count the number of saturated pixels. Operation S140 can be executed by processor 130, but is not limited to this. The number of saturated pixels can be understood as the number of values ​​in the digital signal (i.e., the image) that are greater than or equal to a threshold. System 100 can generate a count value corresponding to a set gain value.

[0108] In operation S150, system 100 can calculate the change in the counted quantity. Operation S150 can be executed by processor 130, but is not limited thereto. For example, system 100 can calculate the change by subtracting the count value generated in a previous operation from the count value generated in operation S140. The count value generated in the previous operation could be a count value corresponding to a gain value smaller than the gain value set in operation S140.

[0109] In operation S160, system 100 can determine whether the gain value is a reference gain value. The reference gain value can be the maximum gain value used for particulate matter measurement. When the current gain value is not the reference gain value, operation S165 is executed. In operation S165, the gain value is increased, and operations S130 to S150 can be executed based on the increased gain value. Operations S130 to S150 can be repeated until the gain value reaches the reference gain value. As a result, count values ​​and changes for multiple different gain values ​​can be calculated.

[0110] In operation S170, system 100 can generate particulate matter data based on the change in count value relative to gain value. Operation S170 can be executed by processor 130, but is not limited thereto. System 100 can calculate the amount of particulate matter within a target size range by applying correction factors to the changes corresponding to the gain value. Here, particulate matter data is understood as the numerical value of the amount of particulate matter before conversion to unit volume.

[0111] In operation S180, system 100 can re-determine whether the conditions for measuring particulate matter are met based on the particulate matter data. As described above with reference to operation S120, when the size of the particulate matter data is greater than a reference value, processor 130 can determine that an object exists in front of sensor 120. When particulate matter measurement is difficult due to this object, system 100 can notify the user of the existence of the object through an output device, and then operation S110 can continue. When no object is detected from sensor 120, operation S190 is executed.

[0112] In operation S190, system 100 can calculate particulate matter concentration by converting particulate matter data into unit volume. Operation S190 can be executed by processor 130, but is not limited thereto. The particulate matter data relates to the amount of particulate matter within at least one target size range. When measuring particulate matter of multiple sizes, the particulate matter data can include values ​​for each of the multiple sizes. System 100 can calculate the concentration for each size of particulate matter by converting each of these values ​​into unit volume.

[0113] Figure 14 This is a flowchart describing a method of operating system 100 according to an exemplary embodiment. Figure 14 The operation can be performed by Figure 1 The system 100 is running. Figure 14 The operation can be performed by system 100, which includes pixels for sensing the visible light band and pixels for sensing the infrared band, such as... Figure 4 The pixel array 121_2. Figure 14 The operation will be understood as a method of selectively performing normal image capture and particulate matter measurement. For ease of description, reference will be made to... Figure 1 Description of reference numerals in the attached figures Figure 14 .

[0114] In operation S210, processor 130 can determine the operating mode of system 100. When an operating mode for normal image capture is selected or determined, operations S220 and S230 are executed. When an operating mode for particulate matter measurement is selected or determined, operations S240 and S250 are executed.

[0115] In operation S220, sensor 120 can generate an image by sensing light in the visible light band. In this case, among multiple pixels, the color pixel that senses light in the visible light band can generate an analog signal based on the sensed light. Conversion circuit 122 can convert the analog signal into a digital signal. Additionally, pixels that sense light in the infrared band (PM pixels) do not sense light in the visible light band.

[0116] In operation S230, system 100 can correct the image corresponding to the PM pixel. Operation S230 can be executed by processor 130, but is not limited thereto. In one example, system 100 can correct the data value corresponding to the PM pixel based on the value corresponding to the color pixel adjacent to the PM pixel. The corrected value can be applied to the image generated in operation S220.

[0117] In operation S240, system 100 can activate illuminator 110. Illuminator 110 can output light to illuminate particulate matter, thereby measuring the concentration of particulate matter. The output light can be scattered by particulate matter. The scattered light can reach sensor 120 or be incident on sensor 120.

[0118] In operation S250, system 100 can measure particulate matter by sensing scattered light. The operation for measuring particulate matter can be combined with... Figure 13 The operations are the same or similar.

[0119] Figure 15 This illustrates an application system 100 (e.g., according to an exemplary embodiment) Figure 1 A diagram illustrating electronic device 200 of system 100. (Refer to...) Figure 15 The electronic device 200 may include a illuminator 210, a sensor 220, and a connector 250. Furthermore, the electronic device 200 may be embedded in or include components related to… Figure 1 The configuration corresponding to processor 130.

[0120] Lighting device 210 can correspond to Figure 1 Illuminator 110. Illuminator 210 can output light in the infrared band to the outside for particulate matter measurement. The output light can be scattered by particulate matter. The scattered light can be incident on sensor 220.

[0121] Sensor 220 can generate an electrical signal for measuring particulate matter based on scattered light. Sensor 220 can correspond to... Figure 1 Sensor 120. Sensor 220 can be arranged adjacent to illuminator 210 to receive light scattered by particles. Sensor 220 can generate an analog signal corresponding to each of different gain values ​​and convert the analog signal into a digital signal.

[0122] Sensor 220 may include Figure 2 The pixel array 121_1. In this case, the electronic device 200 can be a dedicated device for measuring particulate matter. However, it should be understood that one or more other exemplary embodiments are not limited thereto. For example, the sensor 220 may include... Figure 4 The pixel array 121_2. In this case, the electronic device 200 can perform both particulate matter measurement and normal image capture.

[0123] Connector 250 can be provided for electrical connection to external electronic equipment. Through connector 250, electronic equipment 200 can communicate with external devices such as computer equipment. Users can then access particulate matter measurement results via these external devices.

[0124] Electronic device 200 can calculate particulate matter concentrations within a specific size range based on digital signals generated by sensor 220. For this purpose, with... Figure 1 The configuration corresponding to the processor 130 can be provided to the electronic device 200. However, one or more other exemplary embodiments are not limited thereto, and the processor included in the electronic device 200 can control the operation of the illuminator 210 and the sensor 220, and can perform particulate matter measurement in an external device connected via the connector 250.

[0125] Figure 16 This illustrates the application of a system 100 according to another exemplary embodiment (e.g., Figure 1 An exemplary diagram of an electronic device in system 100. (Refer to...) Figure 16 The electronic device 300 may include a illuminator 310 and sensors 321, 322, 323, and 324. The electronic device 300 may include... Figure 1 The components corresponding to processor 130.

[0126] Lighting device 310 can correspond to Figure 1 Illuminator 110. Illuminator 310 can output light in the infrared band to the outside for particulate matter measurement. The output light can be scattered by particulate matter. The scattered light can be incident on at least one of sensors 321, 322, 323 and 324.

[0127] Sensors 321, 322, 323, and 324 can receive external light and convert the received external light into electrical signals, such as analog signals. In sensors 321, 322, 323, and 324, at least one of focal length, viewing angle, number of pixels, and wavelength band of the light to be sensed can be different from each other.

[0128] As an example, the first sensor 321 may be an infrared sensor for sensing depth, and may also be a time-of-flight (TOF) sensor. The first sensor 321 may measure the depth of an object based on reflected light from light output from illuminator 310. Furthermore, the second sensor 322 may be an ultra-wide-angle image sensor having the widest viewing angle and the smallest focal length among sensors 321, 322, 323, and 324. Additionally, the third sensor 323 may be a wide-angle image sensor having a smaller viewing angle and a larger focal length than the second sensor 322. The fourth sensor 324 may be a telephoto image sensor. The second to fourth sensors 322, 323, and 324 may include pixels for sensing light in the visible light band. It should be understood that the above-described types and numbers of sensors 321, 322, 323, and 324 are exemplary. One or more other embodiments may have sensors of different types and characteristics than those described, and may provide different numbers of sensors.

[0129] The sensor adjacent to the illuminator 310 can correspond to Figure 1 The sensor 120. For example, the first sensor 321 or the second sensor 322 can perform operations for measuring particulate matter. Furthermore, the second sensor 322 may include... Figure 4 The pixel array 121_2. In this case, the second sensor 322 can selectively perform normal image capture operations and scattered light sensing operations for measuring particulate matter. For example, the first sensor 321 can selectively perform operations for measuring depth and operations for measuring particulate matter.

[0130] Figure 17 This is an exemplary block diagram of an image system 1000 according to an exemplary embodiment. (Refer to...) Figure 17 The imaging system 1000 may include an illuminator 1100, an image sensor 1200, an image signal processor 1300, and an application processor 1400. The imaging system 1000 can be implemented in a variety of ways, such as desktop computers, laptop computers, tablet computers, smartphones, wearable devices, head-mounted devices, smart wearable devices (e.g., smart glasses), portable multimedia players, and digital camera devices.

[0131] The illuminator 1100 can output infrared light to the outside. The illuminator 1100 may include a light source controller 1110 and a light source 1120. The light source controller 1110 and the light source 1120 can correspond to... Figure 1 The light source controller 111 and the light source 112. The light output from the illuminator 1100 can be scattered by particles and incident on the image sensor 1200.

[0132] Image sensor 1200 may include, for example Figure 4 The pixel array 121_2 is shown. The image sensor 1200 may include pixels for sensing light in the infrared band and pixels for sensing light in the visible light band. In normal operation mode, the image sensor 1200 can sense light in the visible light band and generate a digital image signal. In particulate matter measurement mode, the image sensor 1200 can sense the scattered light output from the light source 1120 and generate digital signals corresponding to different gain values.

[0133] The image signal processor 1300 can perform various image processing operations based on the digital signal generated from the image sensor 1200. The image signal processor 1300 can process digital image signals in normal operating mode. For example, the image signal processor 1300 can perform various operations to improve image quality, such as correcting data values ​​corresponding to pixels sensing light in the infrared band. In particulate matter measurement mode, the image signal processor 1300 can calculate the concentration of particulate matter within a desired size range by analyzing the digital signal. This calculation process has been described above.

[0134] Application processor 1400 can control the overall operation of the components of imaging system 1000. Application processor 1400 can handle various operations for operating imaging system 1000. Application processor 1400 can determine normal mode or particulate measurement mode. In normal mode, application processor 1400 can deactivate illuminator 1100 and provide control signals for capturing images from image sensor 1200. In particulate measurement mode, application processor 1400 can activate illuminator 1100 to output light and control the gain value of image sensor 1200.

[0135] According to an exemplary embodiment, the electronic system and imaging system for measuring particulate matter, as well as the method for measuring particulate matter, can measure the concentration of particulate matter for each size.

[0136] Additionally, according to an exemplary embodiment, the function of measuring particulate matter can be integrated into or combined with an image system for capturing external images.

[0137] While not limited thereto, exemplary embodiments may be embodied at least in part as computer-readable code on a computer-readable recording medium. A computer-readable recording medium is any data storage device capable of storing data that can subsequently be read by a computer system. Examples of computer-readable recording media include read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage devices. Computer-readable recording media may also be distributed across network-connected computer systems, allowing the computer-readable code to be stored and executed in a distributed manner. Furthermore, exemplary embodiments may be written as computer programs transmitted over a computer-readable transmission medium such as a carrier wave, and received and implemented in a general-purpose or special-purpose digital computer running the program.

[0138] The foregoing description describes exemplary embodiments for implementing the inventive concepts(s). The inventive concepts(s) may include not only the exemplary embodiments described above, but also exemplary embodiments in which the design can be easily or readily modified. Furthermore, the inventive concepts(s) may also include techniques that can be readily modified to implement the exemplary embodiments. Therefore, the scope of the inventive concepts(s) is not limited to the described exemplary embodiments, but should be limited to at least the claims and their equivalents.

Claims

1. An electronic system comprising: Illuminator, configured to output light; The sensor includes a pixel array and a conversion circuit. The pixel array is configured to generate an analog signal based on the scattered light of the output light, and the conversion circuit is configured to convert the analog signal into digital signals corresponding to the gain values. as well as The processor is configured to determine the number of values ​​of a digital signal that are greater than or equal to a threshold, and to determine the concentration of particulate matter having a target size range based on the change in the determined number of values ​​determined according to the change in the gain value. The processor is also configured as follows: For each determined number of values ​​in the digital signal that are greater than or equal to a threshold, a count value corresponding to the gain value is generated. The difference in the count value is determined based on the change in the gain value; as well as The concentration of particulate matter corresponding to the target size range is determined by multiplying the difference value by a correction factor corresponding to the target size range.

2. The electronic system according to claim 1, wherein, The conversion circuit is configured to generate a digital signal by amplifying the analog signal while sequentially increasing the gain value from the smallest first gain value to the largest second gain value.

3. The electronic system according to claim 1, wherein: The analog signal includes image signals corresponding to the gain values ​​respectively, and each of the image signals includes a frame signal of the reference scan number; as well as The pixel array is configured to generate as many frame signals as the reference scan for each gain value.

4. The electronic system according to claim 3, wherein: Each of the digital signals includes a digital frame signal corresponding to a frame signal; as well as The sensor is configured to perform an averaging operation on the digital frame signal to generate a corresponding digital signal for each of the gain values.

5. The electronic system according to claim 1, wherein, The processor is configured as follows: Determine a first number of values ​​greater than or equal to a threshold in the first digital signal corresponding to the first gain value among the gain values; Determine a second number of values ​​greater than or equal to a threshold in the second digital signal corresponding to a second gain value that is greater than the first gain value; and The change corresponding to the second gain value is determined by subtracting the first quantity from the second quantity.

6. The electronic system according to claim 1, wherein: The target size range includes a first range and a second range; as well as The processor is configured to determine a first concentration of particulate matter corresponding to a first range and a second concentration of particulate matter corresponding to a second range based on the changes.

7. The electronic system according to claim 6, wherein, The first range corresponds to PM 10, and the second range corresponds to PM 2.

5.

8. An imaging system, comprising: Pixel array, including: The first pixel is configured to generate a first analog signal based on scattered light corresponding to light of a first wavelength band output from the light source, and The second pixel is configured to generate a second analog signal based on light in a second wavelength band that is smaller than the first wavelength band. The conversion circuit is configured to convert a first analog signal into a first digital signal corresponding to a gain value, and to convert a second analog signal into a second digital signal; and The processor is configured to determine the concentration of particulate matter in the region of the output light based on the number of values ​​of a first digital signal that are greater than or equal to a threshold and the change in said number. The processor is also configured as follows: Determine the number of values ​​in the first digital signal that are greater than or equal to a threshold, in order to generate count values ​​corresponding to the gain values ​​respectively; The difference in the count value is determined based on the change in the gain value; and The concentration of particulate matter corresponding to the target size range is determined by multiplying the difference value by a correction factor corresponding to the target size range.

9. The image system according to claim 8, wherein, The first wavelength band is at least a portion of the infrared band, and the second wavelength band is at least a portion of the visible light band.

10. The imaging system according to claim 8, further comprising: A filter configured to allow light from a first wavelength band and a second wavelength band to pass through, while blocking light from a third wavelength band between the first and second wavelength bands. The pixel array is configured to receive scattered light or light of a second wavelength band through a filter.

11. The image system according to claim 8, wherein, The number of first pixels is less than the number of second pixels, and at least four second pixels are set between two first pixels.

12. The imaging system according to claim 8, wherein: Each of the first pixels includes a first pixel region for receiving light of a first wavelength band and a transparent component disposed on the first pixel region; Each of the second pixels includes a second pixel region for receiving light of a second wavelength band and a color filter disposed on the second pixel region and configured to allow light in a portion of the second wavelength band to pass through; as well as The thickness of the transparent component is the same as the thickness of the color filter.

13. The imaging system according to claim 8, wherein: The target size range includes a first range and a second range, and The processor is configured to determine a first concentration of a first particulate matter having a size within a first range by multiplying the change by a first correction factor, and to determine a second concentration of a second particulate matter having a size within a second range by multiplying the change by a second correction factor.

14. The image system according to claim 8, wherein, The processor is configured as follows: In the first mode, the light source is activated, and the conversion circuit is controlled to generate a first digital signal in the first mode. as well as In the second mode, the light source is deactivated, and the conversion circuit is controlled to generate a second digital signal.

15. The imaging system according to claim 8, wherein, The processor is configured to compensate for the value corresponding to the first pixel based on the second digital signal.

16. A method for measuring particulate matter, the method comprising: An analog signal is generated by sensing the scattered light from the output light. Based on the gain value, the analog signal is converted into a digital signal corresponding to the gain value; Determine the number of values ​​in a digital signal that are greater than or equal to a threshold; as well as The concentration of particulate matter corresponding to at least one target size range is determined based on the determined quantity; Determining the concentration of particulate matter includes: Based on the determined quantity, determine the difference value corresponding to the counted quantity in each of the gain values; and Data for particulate matter corresponding to the at least one target size range is obtained by multiplying the difference value by a correction factor.

17. The method of claim 16, wherein: Light has wavelengths in the infrared band; Generating an analog signal involves converting scattered light into an analog signal using a first pixel of the pixel array that senses light in the infrared band; and The pixel array also includes a second pixel for sensing light in the visible light band.

Images