Image processing method and image processing apparatus

Abstract

To prevent data in an area of a noise image in input image data from being erroneously extracted as output image data.SOLUTION: The data processing device 51 detects one or more frame images from the input image data. When a plurality of frame images are detected, the data processing device 51 derives a data-amount index value for each of a plurality of pieces of target area data that are data of areas inside the plurality of frame images. The data processing device 51 specifies one or more pieces of significant area data in which the data amount index value satisfies a predetermined significance condition among the plurality of pieces of object area data. The data processing device 51 outputs the significant region data in the input image data as output image data.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an image processing method and an image processing device that detects a frame image from input image data and extracts data of the area inside the frame image. [Background technology]

[0002] An image processing device such as an image scanner may have an auto-crop function that extracts data of an area inside a rectangular frame image from the data of a scanned image as output image data.

[0003] It is also known that in the image processing device, when multiple areas are extracted by the auto-crop function, the output order of the data for the multiple areas is set according to the positions of the multiple areas (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2020-14179 Summary of the Invention [Problem to be solved by the invention]

[0005] However, there are cases where a noise image in the input image data is detected as a frame image, and in this case, there is a risk that data in the area of ​​the noise image in the input image data will be erroneously extracted as output image data in the auto-crop function.

[0006] An object of the present invention is to provide an image processing method and an image processing device that can prevent data in a noise image area in input image data from being erroneously extracted as output image data. [Means for solving the problem]

[0007] An image processing method according to one aspect of the present invention includes a data processing device executing a process for detecting one or more rectangular frame images from input image data. The image processing method further includes, when multiple frame images are detected, the data processing device deriving a data amount index value for each of multiple target area data, which is data for areas inside the multiple frame images. The image processing method further includes the data processing device identifying one or more significant area data from the multiple target area data, the data amount index value of which satisfies a predetermined significance condition. The image processing method further includes the data processing device outputting the significant area data from the input image data as output image data. The data amount index value includes one or more of the number of pixels exceeding a reference density in each of the multiple target area data, one or both of the number and size of edge images detected by an edge detection process for each of the multiple target area data, the amount of color data included in each of the multiple target area data, the number of character images detected by a character detection process for each of the multiple target area data, and a value representing the detection status of text lines for each of the multiple target area data through document layout analysis.

[0008] An image processing device according to another aspect of the present invention includes an image data acquisition device that acquires image data, and a data processing device that realizes the image processing method by processing the data acquired by the image data acquisition device as the input image data. [Effects of the Invention]

[0009] According to the present invention, it is possible to provide an image processing method and an image processing device that can prevent data in a noise image area in input image data from being erroneously extracted as output image data. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram showing the configuration of an image processing apparatus according to the first embodiment. [Figure 2]FIG. 2 is a diagram showing the configuration of an image reading device in the image processing device according to the first embodiment. [Figure 3] FIG. 3 is a block diagram showing the configuration of a plurality of processing modules included in the image processing unit in the image processing apparatus according to the first embodiment. [Figure 4] FIG. 4 is a block diagram showing the configuration of an image processing apparatus according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Note that the following embodiment is an example of the present invention, and does not limit the technical scope of the present invention.

[0012] [First embodiment] The image processing device 10 according to the first embodiment is capable of executing various types of image processing such as image formation processing, image reading processing, image transmission processing, etc. For example, the image processing device 10 is a copying machine, a facsimile machine, a multifunction peripheral, or the like.

[0013] In the example shown in FIG. 1, an image processing apparatus 10 includes an image reading device 1, a printing device 2, a user interface device 3, a communication device 4, a control device 5, and a secondary storage device 6.

[0014] The image processing device 10 is capable of communicating with other devices such as a host device 8 through a network 80. The network 80 includes a LAN (Local Area Network) and the Internet.

[0015] The image reading device 1 executes the image reading process, which is a process of reading an image from an original 91 and outputting data of the read image.

[0016] The image processing device 10 also includes a frame memory 1x capable of storing image data. The image reading device 1 outputs the data of the read image to the frame memory 1x. The read image is an image read from an original 91.

[0017] The printing device 2 executes the image forming process by a predetermined method such as an electrophotographic method or an inkjet method. The image forming process is a process of forming an image on a sheet 92.

[0018] The printing device 2 includes a sheet transport mechanism that transports a sheet 92 and a printing device that forms an image on the sheet 92 .

[0019] The user interface device 3 includes an operation device 3a and a display device 3b. The operation device 3a is a device that accepts human operations. For example, the operation device 3a includes operation buttons and a touch panel. The display device 3b is capable of displaying information. For example, the display device 3b includes a display panel such as a liquid crystal panel.

[0020] The communication device 4 is a communication interface device that communicates with other devices such as a host device 8 via a network 80. The control device 5 performs all data transmission and reception with the other devices through the communication device 4.

[0021] The printing device 2 executes the image forming process based on the data of the scanned image or the received print data. The received print data is data included in a print request received from the host device 8 via the communication device 4.

[0022] The communication device 4 is also capable of executing the image transmission process, which is a process of transmitting the data of the scanned image to a specified destination via the network 80.

[0023] The control device 5 executes various calculations, data processing, and control of various electrical devices included in the image processing device 10. The control device 5 includes a CPU 51, a RAM (Random Access Memory) 52, and the like.

[0024] The secondary storage device 6 is a computer-readable non-volatile storage device. The secondary storage device 6 can store computer programs and various data. For example, one or both of an SSD (Solid State Drive) and a hard disk drive may be used as the secondary storage device 6.

[0025] The secondary storage device 6 stores the computer programs executed by the CPU 51 and data referenced by the CPU 51. The CPU 51 is an example of a processor.

[0026] The CPU 51 is a processor that executes the computer programs stored in the secondary storage device 6 to perform various data processing and control operations.

[0027] It is also conceivable that another processor such as a DSP may perform the data processing and control instead of the CPU 51.

[0028] The RAM 52 is a computer-readable volatile storage device that temporarily stores the computer programs executed by the CPU 51 and data output and referenced during the execution of the computer programs by the CPU 51.

[0029] The CPU 51 includes a plurality of processing modules that are realized by executing the computer programs, including a job control unit 5a and an image processing unit 5b.

[0030] The job control unit 5a controls the printing device 2, the image reading device 1, and the communication device 4. The job control unit 5a causes some or all of the printing device 2, the image reading device 1, and the communication device 4 to execute a job corresponding to a request input through the operation device 3a or the communication device 4.

[0031] The job includes some or all of the multiple types of image processing, and in this embodiment, the job includes an image scanning job, a print job, and a copy job.

[0032] The image reading job includes the image reading process executed by the operation of the image reading device 1. The print job includes the image forming process executed by the operation of the printing device 2. The copy job includes the image reading process and the image forming process executed by the operations of the image reading device 1 and the printing device 2. In other words, the job includes one or more types of image processing.

[0033] The image processing unit 5b performs various image processing on the image data stored in the frame memory 1x. In this embodiment, the image processing unit 5b performs auto-crop processing to extract data of the area inside a rectangular frame image from the image data stored in the frame memory 1x as output image data.

[0034] Furthermore, the image processing unit 5b also executes image data compression processing for compressing the output image data obtained by the auto-crop processing.

[0035] For example, the image reading job includes the image reading process, the auto-crop process, and the image data compression process executed by the image processing unit 5b. In this case, the image processing unit 5b extracts data of the area inside the frame image from the data of the read image stored in the frame memory 1x, compresses the extracted image data, and outputs the compressed image data.

[0036] Furthermore, the image reading job includes an image data saving process for saving the compressed image data in a secondary storage device 6, or an image transmission process for transmitting the compressed image data to another device such as a host device 8 via a communication device 4.

[0037] As shown in FIG. 2, the image reading device 1 includes a main body 101, a document cover 102, a scanning unit 11, a unit driving device 12, a platen glass unit 13a, a contact glass unit 13b, an AFE (Analog Front End) 14, and a document transport device 15.

[0038] The scanning unit 11 includes a first CIS unit (Contact Image Sensor Unit) 1a. The longitudinal direction of the scanning unit 11 and the first CIS unit 1a is the main scanning direction SD1.

[0039] 2, the direction into the drawing is the main scanning direction SD1, and the direction to the left and right is the sub-scanning direction SD2, which is perpendicular to the main scanning direction SD1.

[0040] The main body 101 is a housing that houses the scanning unit 11 and the unit driving device 12. The platen glass portion 13a and the contact glass portion 13b form part of the top surface of the main body 101.

[0041] The platen glass 13a and the contact glass 13b are transparent plates. The platen glass 13a is a platen on which the document 91 is placed. In this embodiment, one transparent glass plate 13 includes the platen glass 13a and the contact glass 13b.

[0042] The scanning unit 11 is supported by the main body 101. The scanning unit 11 is supported so as to be movable along the sub-scanning direction SD2 in a movable region extending below the platen glass portion 13a and below the contact glass portion 13b.

[0043] The unit driving device 12 moves the scanning unit 11 in the sub-scanning direction SD2 within the movable region.

[0044] The document cover 102 is supported so as to be rotatable between a closed position and an open position. In the closed position, the document cover 102 covers the upper surfaces of the platen glass 13a and the contact glass 13b. In the open position, the document cover 102 exposes the upper surfaces of the platen glass 13a and the contact glass 13b.

[0045] The image reading device 1 is capable of executing a stationary document reading process. In the stationary document reading process, the scanning unit 11 moves along the platen glass portion 13a, and the first CIS unit 1a reads an image of the document 91 placed on the platen glass portion 13a.

[0046] The document transport device 15 is provided on the document cover 102. The document transport device 15 sends out the document 91 on the supply tray 151 to the transport path 150. The document transport device 15 then transports the document 91 along the transport path 150 that passes over the upper surface of the contact glass portion 13b. The document transport device 15 then discharges the document 91 from the transport path 150 onto the discharge tray 152.

[0047] The image reading device 1 can perform a transported document reading process with the document cover 102 closed. In the transported document reading process, the unit drive device 12 holds the scanning unit 11 below the contact glass portion 13b, and the document transport device 15 transports the document 91 along the transport path 150. Furthermore, the first CIS unit 1a reads the image on the underside of the document 91 passing over the contact glass portion 13b.

[0048] The image reading device 1 further includes a second CIS unit 1b provided on the document cover 102. The longitudinal direction of the second CIS unit 1b is the main scanning direction SD1. The second CIS unit 1b is disposed opposite the contact glass portion 13b.

[0049] In the transported document reading process, the second CIS unit 1b reads an image on the upper surface of the document 91 passing over the contact glass portion 13b.

[0050] Each of the first CIS unit 1a and the second CIS unit 1b irradiates light onto the original 91 and detects the amount of light reflected by the original 91. Each of the first CIS unit 1a and the second CIS unit 1b outputs a line image signal Ia0 representing the detection result of the amount of reflected light to the AFE 14.

[0051] In this embodiment, the first CIS unit 1a and the second CIS unit 1b each include a CMOS-type line sensor. Alternatively, one or both of the first CIS unit 1a and the second CIS unit 1b may be replaced with an image sensor unit including a CCD-type image sensor.

[0052] The AFE 14 converts the analog line image signal Ia0 into digital line image data Id0 and stores the line image data Id0 in the frame memory 1x. The line image data Id0 includes a plurality of pixel data for one line in the main scanning direction SD1.

[0053] Line image data Id0 for a plurality of lines corresponding to one page of the document 91 is data of the read image corresponding to one page of the document 91.

[0054] Each of the first CIS unit 1a and the second CIS unit 1b reads a color image of the document 91. Therefore, the read image data is color image data that represents the amount of reflected light of the three colors of red, green, and blue.

[0055] In the following description, the image data to be subjected to the auto-crop process will be referred to as input image data D1 (see FIG. 3).

[0056] However, in the auto-crop process, a noise image in the input image data D1 may be detected as a frame image, and in this case, data in the area of ​​the noise image in the input image data D1 may be erroneously extracted as output image data D2.

[0057] As will be described later, the auto-crop process executed by the image processing unit 5b includes a process for preventing data in the noise image area from being erroneously extracted as output image data D2.

[0058] [Auto Crop Processing] An example of the auto-crop processing by the image processing unit 5b will be described below with reference to Fig. 3. Fig. 3 shows the configuration of a plurality of processing modules included in the image processing unit 5b.

[0059] For example, the input image data D1 to be subjected to the auto-crop process is data of the read image obtained by the image reading device 1 performing the still document reading process.

[0060] The input image data D1 may be image data acquired from the host device 8 by the communication device 4. The input image data D1 may also be data of the read image obtained by the image reading device 1 performing the transported document reading process.

[0061] The image reading device 1 and the communication device 4 are each an example of an image data acquisition device that acquires input image data D1.

[0062] The plurality of processing modules in the image processing unit 5 b include an edge image detection unit 501 , a frame image detection unit 502 , a data amount derivation unit 503 , a significant region specification unit 504 , and a data compression unit 505 .

[0063] The auto-crop processing is executed by an edge image detection unit 501 , a frame image detection unit 502 , a data amount derivation unit 503 , a significant region specification unit 504 , and a data compression unit 505 .

[0064] The auto-crop process is an example of a process that realizes an image processing method. The CPU 51 including the image processing unit 5b is an example of a data processing device that realizes the image processing method.

[0065] The edge image detection unit 501 detects an edge image made up of a plurality of edge pixels by performing edge detection processing on the input image data D1, and outputs edge data D11 representing the detected edge image.

[0066] For example, the edge detection process includes a differential value derivation process and an edge data derivation process. The differential value derivation process is a process of deriving differential values ​​in the X-axis direction and the Y-axis direction for a plurality of pixels in the input image data D1. The edge data derivation process is a process of deriving data consisting of the logical sum of binary data of the differential value in the X-axis direction and binary data of the differential value in the Y-axis direction for each of the plurality of pixels as edge data D11.

[0067] The frame image detection unit 502 executes a frame image detection process to detect one or more rectangular frame images from the edge data D11.

[0068] For example, the frame image detection unit 502 detects one or more first linear images along the X-axis direction and one or more second linear images along the Y-axis direction from the edge data D11.

[0069] The frame image detection unit 502 detects, as the first line image, a line image whose angle with respect to the X-axis direction falls within a predetermined allowable range. Similarly, the frame image detection unit 502 detects, as the second line image, a line image whose angle with respect to the Y-axis direction falls within the allowable range.

[0070] Furthermore, the frame image detection unit 502 detects a rectangular image formed by the two first line images and the two second line images as the frame image. The processing by the edge image detection unit 501 and the frame image detection unit 502 is an example of processing for detecting one or more rectangular frame images from the input image data D1.

[0071] When the number of frame images detected from the edge data D11 is one, the frame image detection unit 502 extracts single frame region data D12, which is data of the region inside the frame image, from the input image data D1.

[0072] On the other hand, when a plurality of frame images are detected from the edge data D11, the frame image detection unit 502 extracts a plurality of target region data D13, which is data on the regions inside the plurality of frame images in the input image data D1.

[0073] The data amount derivation unit 503 derives a data amount index value V1 for each of the plurality of target region data D13.

[0074] In this embodiment, the data amount index value V1 includes one or more of the number of significant pixels, the number of edge images, the edge image size, the amount of colored data, the number of character images, and the number of text lines.

[0075] The number of significant pixels is the number of pixels exceeding the reference density in each of the plurality of target region data D13.

[0076] The number of edge images is the number of edge images detected by the edge detection process for each of the plurality of target region data D13. For example, the data amount derivation unit 503 detects, as the edge images, a plurality of consecutive edge pixels in the edge data D11 that exceeds a predetermined number.

[0077] The edge image size is the size of the edge image. For example, the data amount derivation unit 503 derives the area of ​​a circumscribing rectangle of the edge image or the sum of the lengths of two or four sides of the circumscribing rectangle of the edge image as the edge image size.

[0078] The chromatic data amount is the amount of chromatic data included in each of the plurality of target region data D13. For example, the data amount derivation unit 503 derives the maximum pixel value of the red, green, and blue data for each pixel in each of the plurality of target region data D13, and derives the number of pixels whose maximum pixel value exceeds a reference pixel value as the chromatic data amount.

[0079] The number of character images is the number of character images detected by character detection processing for each of the plurality of target area data D13.

[0080] The number of text lines is the number of text lines detected by document layout analysis for each of the plurality of target area data D13. The number of text lines is an example of a value representing the detection status of the text lines detected by the document layout analysis.

[0081] The significant region identifying unit 504 identifies one or more significant region data D14 whose data amount index value V1 satisfies a predetermined significance condition from among the plurality of target region data D13.

[0082] Here, the index values ​​that exceed the predetermined reference values ​​for the number of significant pixels, the number of edge images, the edge image size, the amount of colored data, the number of character images, and the number of text lines are referred to as significance index values.

[0083] A first example of the significance condition is that the number of significance index values ​​exceeds a predetermined reference number.

[0084] Furthermore, the number of significant pixels, the number of edge images, the edge image size, the amount of color data, the number of character images, and the number of text lines may be dimensionless index values ​​that are non-dimensionalized within a predetermined numerical range. In this case, a second example of the significance condition is a condition that the average or weighted average of the plurality of dimensionless index values ​​exceeds a predetermined reference value.

[0085] A third example of the significance condition is a condition that the non-dimensional index value is the largest one of the plurality of non-dimensional index values.

[0086] When the single frame area data D12 is output by the frame image detection unit 502, the data compression unit 505 compresses the single frame area data D12 using a predetermined compression method, and outputs the compressed data as output image data D2.

[0087] On the other hand, if one or more significant region data D14 are identified by the significant region identification unit 504, the data compression unit 505 compresses the significant region data D14 using a predetermined compression method and outputs one or more compressed data as output image data D2.

[0088] For example, the data compression unit 505 compresses the data using a compression method such as the JPEG method, the GIF method, or the PDF method.

[0089] The data compression unit 505 may be replaced with an image output unit that outputs uncompressed output image data D2. In this case, the image output unit outputs the single frame region data D12 or the significant region data D14 as the output image data D1.

[0090] By employing the image processing device 10, it is possible to prevent data in the noise image area in the input image data D1 from being erroneously extracted as the output image data D2 in many cases.

[0091] [Second embodiment] Next, an image processing device 10A according to a second embodiment will be described with reference to Fig. 4. In Fig. 4, the same components as those shown in Fig. 1 are denoted by the same reference numerals.

[0092] The image processing device 10A has a configuration in which an autocrop circuit 7 is added to the image processing device 10. The autocrop circuit 7 is a circuit that realizes, by hardware, the processes of the edge image detection unit 501, the frame image detection unit 502, the data amount derivation unit 503, the significant region identification unit 504, and the data compression unit 505 shown in FIG.

[0093] That is, the autocrop circuit 7 includes an edge image detection circuit that realizes the processing of the edge image detection unit 501, a frame image detection circuit that realizes the processing of the frame image detection unit 502, a data amount derivation circuit that realizes the processing of the data amount derivation unit 503, a significant area identification circuit that realizes the processing of the significant area identification unit 504, and a data compression circuit that realizes the processing of the data compression unit 505.

[0094] The autocrop circuit 7 is an example of a data processing device that realizes the image processing method. When the image processing device 10A is used, the same effects as when the image processing device 10 is used can be obtained.

[0095] [Notes on the Invention] The following is a summary of the invention extracted from the above-described embodiment. Note that the configurations and processing functions described in the following supplementary notes can be selected and combined as desired.

[0096] <Appendix 1> A data processing device executes a process of detecting one or more rectangular frame images from input image data; When a plurality of the frame images are detected, the data processing device derives a data amount index value for each of a plurality of target area data, which is data of areas inside the plurality of the frame images; The data processing device identifies one or more significant area data from among the plurality of target area data, the data amount index value of which satisfies a predetermined significance condition; the data processing device outputs the significant region data in the input image data as output image data, The data amount index value is the number of pixels exceeding a reference density in each of the plurality of target area data; one or both of the number and size of edge images detected by edge detection processing for each of the plurality of target area data; the amount of color data included in each of the plurality of target region data; and the number of character images detected by the character detection process for each of the plurality of target area data; and a value representing a detection status of a text line by document layout analysis for each of the plurality of target area data.

[0097] <Appendix 2> The image processing method according to claim 1, wherein the data processing device detects rectangular edge pixels from the input image data as the frame image by performing edge detection processing on the input image data.

[0098] <Appendix 3> an image data acquisition device that acquires image data; and a data processing device that implements the image processing method according to Supplementary Note 1 or Supplementary Note 2, which processes data obtained by the image data acquisition device as the input image data.

[0099] <Appendix 4> The image processing device described in Appendix 3, wherein the image data acquisition device is an image reading device having a transparent platen on which a document is placed, reading an image from the document placed on the platen, and outputting data of the read image. [Explanation of symbols]

[0100] 1: Image reader 1a: 1st CIS Unit 1b: 2nd CIS Unit 1x: Frame memory 2: Printing device 5: Control device 7: Auto-crop circuit 10: Image processing device 10A: Image processing device 11: Scanning unit 12: Unit drive device 13: Glass plate 13a: Platen glass part 13b: Contact glass part 14 :AFE 15: Document transport device 150: Transport path D1: Input image data D11: Edge data D12: Single frame area data D13: Target area data D14: Significant region data D2: Output image data

Claims

1. A data processing device executes a process of detecting one or more rectangular frame images from input image data; When a plurality of the frame images are detected, the data processing device derives a data amount index value for each of a plurality of target area data, which is data of areas inside the plurality of the frame images; the data processing device identifies one or more significant area data from among the plurality of target area data, the data amount index value of which satisfies a predetermined significance condition; the data processing device outputs the significant region data in the input image data as output image data, The data amount index value is the number of pixels exceeding a reference density in each of the plurality of target area data; one or both of the number and size of edge images detected by edge detection processing for each of the plurality of target area data; the amount of color data included in each of the plurality of target region data; and the number of character images detected by the character detection process for each of the plurality of target area data; and a value representing a detection status of a text line by document layout analysis for each of the plurality of target area data.

2. 2. The image processing method according to claim 1, wherein the data processing device detects rectangular edge pixels from the input image data as the frame image by performing edge detection processing on the input image data.

3. an image data acquisition device that acquires image data; 3. An image processing apparatus comprising: a data processing apparatus that implements the image processing method according to claim 1 or 2, and processes data obtained by the image data acquisition apparatus as the input image data.

4. 4. The image processing apparatus according to claim 3, wherein the image data acquisition device is an image reading device having a transparent platen on which an original is placed, reading an image from the original placed on the platen, and outputting data of the read image.

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