Pre-oxidation furnace flame detection method and system based on infrared imaging

Abstract

The invention relates to the technical field of carbon fiber production detection, in particular to a pre-oxidation furnace flame detection method and system based on infrared imaging, and the method comprises the steps: obtaining the characteristics of a wind field and a temperature field in a pre-oxidation furnace when the pre-oxidation furnace works, and a yarn movement direction; shooting the interior of the pre-oxidation furnace by using an infrared imaging camera to obtain a temperature image; calculating the temperature change of each point in each direction in the temperature image, and extracting an area with local temperature increasing as a suspected flame area; judging whether the suspected flame area contains three-layer change characteristics of flame temperature characteristics or not, and if not, excluding the suspected flame area; if yes, a plurality of temperature images are continuously shot, whether changes of suspected flame areas in the temperature images conform to the yarn movement direction and the wind field characteristics or not is compared, and if yes, the suspected flame areas are determined to be flame areas. The infrared imaging technology is not interfered by visible light, and the system can cope with complex environmental changes in the production process by combining comprehensive analysis of a temperature field, a wind field and yarn movement.

Description

Technical Field

[0001] The invention relates to the technical field of carbon fiber production detection, and in particular to a pre-oxidation furnace flame detection method and system based on infrared imaging. Background Art

[0002] Carbon fiber is commonly known as black gold in the market. During the production process of carbon fiber, the PAN-based fiber precursor must first undergo oxidation and carbonization processes before it can become real carbon fiber.

[0003] The process of carbon fiber pre-oxidation is to combine oxygen molecules in the air with PAN-based fibers under high temperature environment, so that the polymer chains begin to cross-link, and the fiber density increases from 1.18g / cc to 1.38g / cc. Temperature control is very important. Usually the temperature range of the pre-oxidation furnace is between 200℃ and 300℃. However, in a high temperature environment, if there are joints on the carbon fiber or the temperature field or wind field in the furnace is uneven, the local temperature of the fiber will be too high, causing fire on the tow, which will cause deflagration in the furnace.

[0004] In this case, flame detection in the carbonization wire oxidation furnace is proposed. Conventional flame detection uses a visible light camera to analyze the characteristics of the flame when the pre-oxidation wire burns in the oxidation furnace to detect whether there is a flame in the oxidation furnace. However, in this case, there will be some external interference, such as the flashlight of daily inspection workers, the redness of the pre-oxidation wire and other visible lights. To a certain extent, complex feature analysis is needed to distinguish them, which may require a large number of data samples, affecting the processing speed, thereby reducing the detection speed.

[0005] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0006] The present invention provides a pre-oxidation furnace flame detection method and system based on infrared imaging, thereby effectively solving the problems in the background technology.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a flame detection method for a pre-oxidation furnace based on infrared imaging, comprising the following steps:

[0008] Obtain the wind field and temperature field characteristics inside the pre-oxidation furnace when it is working, as well as the yarn movement direction;

[0009] Use an infrared imaging camera to photograph the interior of the pre-oxidation furnace to obtain a temperature image;

[0010] Calculating the temperature change of each point in the temperature image in each direction, and extracting the area where the local temperature becomes high as the suspected flame area;

[0011] Determine whether the suspected flame area contains the three-layer variation characteristics of the flame temperature feature, and if not, exclude it;

[0012] If so, several temperature images are taken continuously to compare whether the changes of the suspected flame area in the temperature images are consistent with the yarn movement direction and the wind field characteristics. If they are consistent, it is determined to be the flame area.

[0013] Further, the calculating the temperature change of each point in the temperature image in each direction includes:

[0014] Assume the temperature image is g(x, y);

[0015] Calculate the first-order derivative of each point with respect to temperature in all directions, that is:

[0016] Assume that the temperature at the point g(x0, y0) is g0, then the difference in the positive direction of X is g(x0+1, y0)-g(x0, y0);

[0017] Similarly, calculate the difference of each point in the positive and negative directions of X and Y.

[0018] Furthermore, the step of extracting the area where the local temperature becomes high as the suspected flame area comprises the following steps:

[0019] Calculate the global average value of g(x,y) in the initial state as the initial temperature in the pre-oxidation furnace;

[0020] Determine the overall global average temperature of each of the temperature images, and calculate the difference between the overall global average temperature and the initial temperature;

[0021] If there is a point whose temperature change exceeds the set temperature threshold and exceeds the difference between the overall global average temperature and the initial temperature, it is extracted.

[0022] Further, the step of judging whether the suspected flame region contains the three-layer variation characteristics of the flame temperature feature comprises the following steps:

[0023] Calculate the first derivative of the eight neighborhoods of each point in the suspected flame area;

[0024] Determine whether the calculated data includes the three categories of center, inner edge and outer edge, and whether the temperature has a trend of gradually increasing from the center to the inner edge and then to the outer edge.

[0025] Furthermore, comparing the changes of the suspected flame area in the plurality of temperature images to determine whether they are consistent with the yarn movement direction and the wind field characteristics includes:

[0026] Calculating the temperature gradient of the outermost layer of the suspected flame area in each of the temperature images;

[0027] Determining whether the temperature gradient direction of the outermost layer conforms to the wind field characteristics;

[0028] It is determined whether the movement of the temperature gradient is parallel to the yarn movement direction.

[0029] The present invention also includes a pre-oxidation furnace flame detection system based on infrared imaging, using the above method, the detection system comprises:

[0030] An input unit is used to obtain the wind field and temperature field characteristics in the pre-oxidation furnace when it is working, and the yarn movement direction;

[0031] An infrared shooting unit is used to shoot the inside of the pre-oxidation furnace using an infrared imaging camera to obtain a temperature image;

[0032] A suspected flame region extraction unit is used to calculate the temperature change of each point in the temperature image in each direction, and extract the region where the local temperature becomes high as the suspected flame region;

[0033] An interference elimination unit, used to determine whether the suspected flame area contains the three-layer variation characteristics of the flame temperature feature, and if not, eliminate it;

[0034] The flame judgment unit is used to continuously shoot several temperature images if the suspected flame area contains three-layer change characteristics of the flame temperature characteristics, and compare whether the changes of the suspected flame area in the several temperature images are consistent with the yarn movement direction and the wind field characteristics. If they are consistent, it is determined to be a flame area.

[0035] The present invention also includes a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described above is implemented.

[0036] The present invention also includes a storage medium on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0037] The beneficial effects of the present invention are as follows: the infrared imaging technology of the present invention is not affected by visible light, can work stably in a high-temperature, low-light pre-oxidation furnace environment, effectively improves the accuracy of flame detection, and through a comprehensive analysis of the temperature field, wind field and yarn movement, enables the system to cope with complex environmental changes during the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 Flow chart of the method of the present invention

[0040] Figure 2 It is a structural schematic diagram of the system of the present invention;

[0041] Figure 3 It is a schematic diagram of the structure of the computer device of the present invention. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0043] like Figure 1 As shown: A pre-oxidation furnace flame detection method based on infrared imaging includes the following steps:

[0044] Obtain the wind field and temperature field characteristics inside the pre-oxidation furnace when it is working, as well as the yarn movement direction;

[0045] Use an infrared imaging camera to photograph the interior of the pre-oxidation furnace to obtain a temperature image;

[0046] Calculate the temperature change of each point in the temperature image in all directions, and extract the area with local high temperature as the suspected flame area;

[0047] Determine whether the suspected flame area contains the three-layer variation characteristics of the flame temperature feature, if not, exclude it;

[0048] If so, take several temperature images continuously and compare whether the changes of the suspected flame area in the temperature images are consistent with the yarn movement direction and wind field characteristics. If they are consistent, it is determined to be the flame area.

[0049] First, the system needs to understand the working environment inside the pre-oxidation furnace, including the temperature distribution (temperature field) and airflow direction (wind field) inside the furnace, as well as the movement trajectory of the yarn in the furnace. These factors are important bases for subsequent judgments on whether the flame area conforms to the actual situation. The pre-oxidation furnace is photographed in real time by an infrared imaging camera to generate a temperature image. The infrared imaging camera can capture the temperature differences in different areas, thereby providing temperature information for each point in the furnace. The system calculates the temperature changes in different directions for each point in the temperature image to find areas with abnormally high local temperatures. These areas may be caused by flames or other high-temperature phenomena. The goal of this step is to preliminarily lock in suspected flame areas.

[0050] Perform temperature layered analysis on the suspected flame area to determine whether the area meets the three-layer temperature characteristics of the flame. If not, it will be excluded to avoid false alarms. In order to further verify whether the suspected flame area is a real flame, the system will continuously take multiple temperature images to observe the changes in the suspected flame area in these images. By comparing these changes, it is determined whether the movement of the area is consistent with the movement direction of the yarn and the wind field characteristics in the furnace. If the movement pattern of the suspected area is consistent with the yarn and wind field characteristics, the area is finally determined to be a flame.

[0051] Infrared imaging technology is not affected by visible light and can work stably in the high-temperature, low-light pre-oxidation furnace environment, effectively improving the accuracy of flame detection. By combining comprehensive analysis of temperature field, wind field and yarn movement, the system can cope with complex environmental changes during the production process.

[0052] In this embodiment, calculating the temperature change of each point in the temperature image in each direction includes:

[0053] Assume that the temperature image is g(x,y), where x and y represent the horizontal and vertical coordinates of the image respectively, and g(x,y) represents the temperature value at that point;

[0054] Calculate the first-order derivative of each point with respect to temperature in all directions, that is:

[0055] Assume that the temperature at the point g(x0, y0) is g0, then the difference in the positive direction of X is g(x0+1, y0)-g(x0, y0);

[0056] Similarly, calculate the difference of each point in the positive and negative directions of X and Y.

[0057] The temperature change rate of the point in different directions can be calculated by the above differential formula. The first-order derivative of temperature can be used to analyze whether the local temperature has changed significantly, thereby identifying the suspected flame area. By calculating the difference in each direction, the area with rapid changes in local temperature, that is, the possible flame location, can be detected.

[0058] The process of extracting the area where the local temperature becomes high as the suspected flame area includes the following steps:

[0059] Calculate the global average value of g(x,y) in the initial state as the initial temperature in the pre-oxidation furnace;

[0060] Determine the overall global average temperature of each temperature image, and calculate the difference between the overall global average temperature and the initial temperature;

[0061] If the temperature change of a certain point exceeds the set temperature threshold and exceeds the difference between the overall global average temperature and the initial temperature, it will be extracted.

[0062] By calculating the difference between the initial temperature and the current global average temperature, the interference caused by the overall increase in ambient temperature can be effectively filtered out, thereby more accurately identifying local abnormal temperature areas. Setting a temperature threshold can flexibly adjust the system's sensitivity to flames to avoid false alarms or missed alarms. By comparing the difference between local temperature changes and global temperature changes, this method can adapt to the fluctuations in the temperature field inside the pre-oxidation furnace and reduce misjudgments of temperature anomalies caused by wind fields or other factors.

[0063] As a preferred embodiment of the above, judging whether the suspected flame area contains the three-layer variation characteristics of the flame temperature feature includes the following steps:

[0064] Calculate the first derivative of the eight-neighborhood of each point in the suspected flame area;

[0065] Determine whether the calculated data includes the three categories of center, inner edge and outer edge, and whether the temperature has a trend of gradually increasing from the center to the inner edge and then to the outer edge.

[0066] Determine whether the data contains the three-layer structure of flame: The center of a suspected flame area is usually the point with the highest temperature in the area. At this time, the temperature of the center point should be significantly higher than the surrounding neighboring points. The temperature of the circle of neighboring points around the center point, that is, 8 neighboring points, is usually lower than the center point but higher than the outer edge. The temperature of the outer points should be significantly lower than the inner edge.

[0067] For each suspected flame area, determine whether its temperature change conforms to the following trend: from the center point to the inner edge, and then to the outer edge, the temperature should gradually decrease. By comparing the temperature values ​​of the center, inner edge, and outer edge, this trend of temperature change is detected. If it conforms to this pattern, the area has the temperature characteristics of a flame.

[0068] By analyzing the three-layer temperature structure of the flame, the influence of external interference factors such as reflected light and mechanical heat sources on flame detection can be effectively avoided. By calculating the temperature derivative of the local eight-neighborhood, the edge change characteristics of the flame are captured, which helps to more accurately distinguish the flame from other high-temperature points. Since the temperature change of the flame has a specific hierarchy, judging by multi-level temperature differences can reduce false alarms of other temperature field fluctuations.

[0069] As a preferred embodiment of the above, comparing the changes of the suspected flame area in the plurality of temperature images to see whether they are consistent with the yarn movement direction and wind field characteristics includes:

[0070] Calculate the temperature gradient of the outermost layer of the suspected flame area in each temperature image;

[0071] Determine whether the direction of the temperature gradient of the outermost layer conforms to the wind field characteristics;

[0072] Determine whether the movement of the temperature gradient is parallel to the direction of yarn movement.

[0073] For each suspected flame area in the temperature image, find the outermost boundary point of the area, that is, the area where the temperature is significantly reduced, calculate these gradient values, and obtain the direction and rate of change of the outermost temperature. The wind field characteristics in the pre-oxidation furnace are usually manifested as airflow in a certain direction. The outer temperature gradient of the flame area should conform to this airflow direction.

[0074] The temperature gradient is calculated as:

[0075]

[0076] By directing the temperature gradient With known wind direction By comparison, it can be determined whether the temperature of the flame area is spreading along the direction of the airflow. The specific judgment method is:

[0077]

[0078] When cosφ≈1, it means that the moving direction of the suspected flame area is consistent with the yarn movement direction, which further verifies that the area is the flame area.

[0079] If the temperature gradient direction of the suspected flame area is consistent with the wind field direction, and its movement trend is parallel to the yarn movement direction, it can be confirmed that the area meets the characteristics of the flame. By analyzing multiple continuous images, not only can the static temperature characteristics be judged, but also the accuracy of judgment can be further improved based on the dynamic changes of the flame with the wind field and yarn movement. In the high temperature and high wind speed environment of the pre-oxidation furnace, the shape of the flame changes rapidly. By combining the temperature gradient and dynamic movement characteristics, it is possible to respond quickly and accurately identify the flame.

[0080] like Figure 2 As shown, this embodiment also includes a pre-oxidation furnace flame detection system based on infrared imaging. Using the above method, the detection system includes:

[0081] An input unit is used to obtain the wind field and temperature field characteristics in the pre-oxidation furnace when it is working, and the yarn movement direction;

[0082] An infrared shooting unit is used to shoot the inside of the pre-oxidation furnace using an infrared imaging camera to obtain a temperature image;

[0083] A suspected flame region extraction unit is used to calculate the temperature change of each point in the temperature image in all directions, and extract the region where the local temperature becomes high as the suspected flame region;

[0084] The interference elimination unit is used to determine whether the suspected flame area contains the three-layer variation characteristics of the flame temperature characteristics, and if not, it is eliminated;

[0085] The flame judgment unit is used to continuously shoot several temperature images if the suspected flame area contains three-layer change characteristics of the flame temperature characteristics, and compare whether the changes of the suspected flame area in the several temperature images are consistent with the yarn movement direction and wind field characteristics. If they are consistent, it is determined to be a flame area.

[0086] See also Figure 3 A computer device 400 provided in an embodiment of the present application includes: a processor 410 and a memory 420, wherein the memory 420 stores a computer program executable by the processor 410, and when the computer program is executed by the processor 410, the above method is executed.

[0087] The embodiment of the present application further provides a storage medium 430 on which a computer program is stored. When the computer program is run by the processor 410, the above method is executed.

[0088] Among them, the storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0089] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0090] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0091] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0092] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0093] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0094] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0095] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0096] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A pre-oxidation furnace flame detection method based on infrared imaging, characterized in that: The steps include: Obtain the wind field and temperature field characteristics inside the pre-oxidation furnace when it is working, as well as the yarn movement direction; Use an infrared imaging camera to photograph the interior of the pre-oxidation furnace to obtain a temperature image; Calculating the temperature change of each point in the temperature image in each direction, and extracting the area where the local temperature becomes high as the suspected flame area; Determine whether the suspected flame area contains the three-layer variation characteristics of the flame temperature feature, and if not, exclude it; If so, several temperature images are taken continuously to compare whether the changes of the suspected flame area in the temperature images are consistent with the yarn movement direction and the wind field characteristics. If they are consistent, it is determined to be the flame area.

2. The pre-oxidation furnace flame detection method based on infrared imaging according to claim 1 is characterized in that: The calculating the temperature change of each point in the temperature image in each direction comprises: Assume the temperature image is g(x, y); Calculate the first-order derivative of each point with respect to temperature in all directions, that is: Assume that the temperature at the point g(x0, y0) is g0, then the difference in the positive direction of X is g(x0+1, y0)-g(x0, y0); Similarly, calculate the difference of each point in the positive and negative directions of X and Y.

3. The pre-oxidation furnace flame detection method based on infrared imaging according to claim 2 is characterized in that: The step of extracting the area where the local temperature becomes high as the suspected flame area comprises the following steps: Calculate the global average value of g(x,y) in the initial state as the initial temperature in the pre-oxidation furnace; Determine the overall global average temperature of each of the temperature images, and calculate the difference between the overall global average temperature and the initial temperature; If there is a point whose temperature change exceeds the set temperature threshold and exceeds the difference between the overall global average temperature and the initial temperature, it is extracted.

4. The pre-oxidation furnace flame detection method based on infrared imaging according to claim 1 is characterized in that: The step of judging whether the suspected flame area contains the three-layer variation characteristics of the flame temperature feature comprises the following steps: Calculate the first derivative of the eight neighborhoods of each point in the suspected flame area; Determine whether the calculated data includes the three categories of center, inner edge and outer edge, and whether the temperature has a trend of gradually increasing from the center to the inner edge and then to the outer edge.

5. The pre-oxidation furnace flame detection method based on infrared imaging according to claim 1 is characterized in that: The comparing whether the change of the suspected flame area in the plurality of temperature images is consistent with the yarn movement direction and the wind field characteristics includes: Calculating the temperature gradient of the outermost layer of the suspected flame area in each of the temperature images; Determining whether the temperature gradient direction of the outermost layer conforms to the wind field characteristics; It is determined whether the movement of the temperature gradient is parallel to the yarn movement direction.

6. A flame detection system for a pre-oxidation furnace based on infrared imaging, characterized in that: Using the method according to any one of claims 1 to 5, the detection system comprises: An input unit is used to obtain the wind field and temperature field characteristics in the pre-oxidation furnace when it is working, and the yarn movement direction; An infrared shooting unit is used to shoot the inside of the pre-oxidation furnace using an infrared imaging camera to obtain a temperature image; A suspected flame region extraction unit is used to calculate the temperature change of each point in the temperature image in each direction, and extract the region where the local temperature becomes high as the suspected flame region; An interference elimination unit, used to determine whether the suspected flame area contains the three-layer variation characteristics of the flame temperature feature, and if not, eliminate it; The flame judgment unit is used to continuously shoot several temperature images if the suspected flame area contains three-layer change characteristics of the flame temperature characteristics, and compare whether the changes of the suspected flame area in the several temperature images are consistent with the yarn movement direction and the wind field characteristics. If they are consistent, it is determined to be a flame area.

7. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

8. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

Images