JP2013197889A - Image processing device and image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing device that is capable of, even when an image is recompressed, detecting the presence or absence of an alteration while preventing erroneous detection of the alteration.SOLUTION: An image processing device includes: a frequency conversion part for converting an image into a frequency conversion coefficient; and a quantization part for calculating a quantization frequency conversion coefficient by quantizing the frequency conversion coefficient based on a first quantization table. The image processing device further includes: a generation part for generating an alteration detection code for detection of an alteration based on the minimum invariable coefficient stipulated by a coefficient that is one of the frequency conversion coefficient and the quantization frequency conversion coefficient, whose absolute value is the minimum value, and whose minimum value does not change even when the frequency conversion coefficient is quantized based on an arbitrary quantization table other than the first quantization table.

Description

  The present invention relates to an image processing apparatus and an image processing method for preventing or detecting falsification of content such as an image.

  In recent years, with the development of digital image processing technology and the advent of cameras capable of digital photography, the usage scenes of digital still images and digital images (hereinafter referred to as images together) have increased dramatically. Unlike a conventional silver halide photograph, a photographed image can be easily changed using image editing software on a personal computer. For this reason, it is important to accurately detect the presence or absence of tampering in images that require evidence, such as drive recorders, surveillance video, and photographs of construction reports. .

  As a method of detecting the presence / absence of image falsification, calculate the hash value of the original image that has not been falsified, calculate the same hash value for the image you want to detect falsification, and match or mismatch the hash values. A technique for determining falsification of an image is disclosed.

  The above-described disclosed technique creates robust digital signature data serving as verification data for image tampering detection, and performs image tampering detection using the created robust digital signature data. Specifically, a feature amount that does not change is calculated from an original image that has not been tampered with when the image does not change substantially. As a specific feature amount, a quantized DCT coefficient is calculated for each DCT coefficient block. Then, a hash value of the quantized DCT coefficient is calculated using a hash function. Thereafter, a digital signature is performed using the secret key, and robust digital signature data is output.

  When detecting the presence or absence of falsification of an image, a hash value is calculated from robust digital signature data using a public key. Also, a quantized DCT coefficient that is a feature amount of the image is calculated from the image to be detected for falsification, and a hash value of the quantized DCT coefficient is calculated. Finally, the hash value calculated from the robust digital signature data is compared with the hash value calculated from the quantized DCT coefficient of the image to be tampered with. If the hash values are different, it is determined that the image has been tampered with.

  In the above disclosed technique, for example, when an image such as rewriting the color of a signal so as to be advantageous to a photograph of a traffic accident is corrected, the image is altered or the alteration is detected. Is possible.

Patent No. 4454908

  By the way, with the increase of the use scene of an image, the recompression which recompresses the compressed image is performed frequently by the restriction | limiting of the storage capacity of a storage apparatus. This is because the tampering detection target image is often set at a low compression rate in order to improve the image quality. However, when such an image is stored in a storage device, there is often a desire to reduce the storage capacity as much as possible even if the image quality is reduced by recompression.

  The compression rate is uniquely determined by the coefficient of the quantization table. That is, if the compression rate is different, the quantization table is different. Here, for example, when recompression is performed using the quantization table B for an image such as a JPEG image quantized by the quantization table A, the quantization table is different before and after the recompression. Quantized frequency transform coefficients such as quantized DCT coefficients also differ before and after recompression.

  For this reason, the hash value A of the quantization frequency conversion coefficient calculated by the hash function from the image before recompression is different from the hash value B of the quantization frequency conversion coefficient calculated by the hash function from the image after recompression. End up. For this reason, when the image is recompressed including the above-described disclosed technique, the hash value is different before and after the recompression even though the essential content of the image does not change. For this reason, there is a problem that the image is erroneously detected as being falsified even though the image is not falsified.

  An object of the present invention is to provide an image processing apparatus that can detect the presence or absence of falsification without erroneously detecting falsification even when the image is recompressed.

  An image processing apparatus according to an aspect disclosed by the present invention calculates a quantized frequency transform coefficient by quantizing a frequency transform coefficient based on a first quantization table and a frequency transform unit that transforms an image into a frequency transform coefficient. A quantization unit is provided. Further, the image processing apparatus quantizes the frequency transform coefficient based on an arbitrary quantization table other than the first quantization table, and the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value. In this case, a generation unit that generates a falsification detection code for detecting falsification based on a minimum invariant coefficient defined by a coefficient whose minimum value does not change is provided.

  An image processing apparatus according to another aspect disclosed by the present invention acquires a quantized frequency transform coefficient in which an image is converted into a frequency transform coefficient, and the frequency transform coefficient is quantized based on a first quantization table. Even if the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table, the minimum value A generation unit that generates a first falsification detection code that detects falsification based on a minimum invariant coefficient defined by a coefficient that does not change. The image processing apparatus further includes a comparison unit that acquires the second falsification detection code generated based on the minimum invariant coefficient and compares the first falsification detection code and the second falsification detection code.

  The objects and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. It should also be understood that both the above general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention as claimed.

  In the image processing apparatus disclosed in this specification, even when an image is recompressed, it is possible to detect the presence or absence of falsification without erroneously detecting falsification.

It is a figure which shows an example of a structure of the image processing apparatus 10 by one Embodiment. 3 is a functional block diagram illustrating an example of a control unit 11 in Embodiment 1. FIG. The DCT conversion coefficient which is an example of the frequency conversion coefficient of a compressed image is shown. The 1st quantization table used as an example of a quantization table is shown. The quantization DCT coefficient which is an example of a quantization frequency conversion coefficient is shown. A quantized DCT coefficient is shown as an example of a quantized frequency transform coefficient quantized with an arbitrary quantization table different from the first quantization table for recompression. (A) shows the frequency conversion coefficient of an original image. (B) shows the quantization frequency conversion coefficient which converted the frequency conversion coefficient of (a) using the 1st quantization table. (C) converts the frequency conversion coefficient of (a) using an arbitrary first quantization table other than the first quantization table, and converts the quantized frequency conversion coefficient in which a part of the coefficient is tampered with Show. (A) is the conceptual diagram which converted the position of the minimum invariant coefficient of the quantization frequency coefficient of the quantization frequency conversion coefficient block of the original original image into (alpha). (B) shows an example of a falsification detection code. The correspondence table of the range of the quantization frequency conversion coefficient value and the falsification detection code is shown. A conceptual diagram of the zigzag scanning method is shown. The conceptual diagram of a vertical direction priority scanning system is shown. 3 is a flowchart illustrating an example of falsification prevention processing according to the first exemplary embodiment. It is a figure which shows an example of a structure of the image processing apparatus 30 by one Embodiment. FIG. 10 is a functional block diagram illustrating an example of a control unit 31 according to a second embodiment. 10 is a flowchart (part 1) illustrating an example of falsification detection processing according to the second embodiment. 12 is a flowchart (part 2) illustrating an example of falsification detection processing according to the second embodiment. FIG. 10 is a functional block diagram illustrating an example of a control unit 31 according to a third embodiment. 12 is a flowchart illustrating an example of falsification detection processing in the third embodiment. FIG. 10 is a functional block diagram illustrating an example of a control unit 11 according to a fourth embodiment.

  Hereinafter, examples of an image processing apparatus, an image processing method, and an image processing computer program according to an embodiment will be described in detail with reference to the drawings. Note that this embodiment does not limit the disclosed technology.

Example 1
FIG. 1 is a diagram illustrating an example of a configuration of an image processing apparatus 10 according to one embodiment. The image processing apparatus 10 illustrated in FIG. 1 also functions as a falsification preventing apparatus that prevents falsification of an image. An image processing apparatus 10 illustrated in FIG. 1 includes a control unit 11, a main storage unit 12, an auxiliary storage unit 13, a display control unit 14, a recording medium I / F unit 16, and a camera I / F unit 18. Each unit is connected to each other via a bus so that data can be transmitted and received.

  The control unit 11 is a CPU (Central Processing Unit) that controls each device, calculates data, and processes in the computer. The control unit 11 is an arithmetic device that executes a program stored in the main storage unit 12 or the auxiliary storage unit 13. The control unit 11 receives data from each storage unit, calculates and processes the data, and then outputs the data to the output unit and each storage unit.

  Further, for example, the control unit 11 plays a role of an anti-tampering function for an image by executing an image processing program that functions as an anti-tampering program stored in the auxiliary storage unit 13.

  The main storage unit 12 is, for example, a RAM (Random Access Memory), and is a storage unit that stores or temporarily stores programs and data such as an OS and application software that are basic software executed by the control unit 12. The main storage unit 12 functions as a work memory for storing programs and data.

  The auxiliary storage unit 13 is, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and is a storage device that stores data related to application software. The auxiliary storage unit 13 stores a falsification preventing program.

  The auxiliary storage unit 13 stores an image acquired from the camera I / F unit 18. The auxiliary storage unit 13 may store an image acquired from the recording medium 17 or the like.

  The display control unit 14 performs display control in order to display images and data on the display unit 15.

  The recording medium I / F (interface) unit 16 is an interface between the image processing apparatus 10 and a recording medium 17 (for example, a flash memory) connected via a data transmission path such as a USB (Universal Serial Bus).

  A predetermined program (image processing program) is stored in the recording medium 17, and the program stored in the recording medium 17 is installed in the image processing apparatus 10 via the recording medium I / F unit 16. The installed predetermined program can be executed by the image processing apparatus 10.

When the recording medium 17 is an SD card, for example, the recording medium I / F unit 16 is an SD card slot.

  The camera I / F unit 18 acquires an image captured by the camera 19. The acquired image is stored in the main storage unit 12. The camera 19 and the display unit 15 may be built in the image processing apparatus 10.

  In addition, the image processing apparatus 10 includes a communication unit (not shown) and performs wired or wireless communication. For example, the communication unit transmits a compressed image, a public key, an electronic signature, and the like to an external device or the like.

(Falsification prevention function)
Next, the control unit 11 will be described in detail. FIG. 2 is a functional block diagram illustrating an example of the control unit 11 according to the first embodiment. 2 includes a block dividing unit 21,
The frequency converter 22, the quantizer 23, the variable length encoder 24, the invariant coefficient position detector 25, the generator 26, and the signature generator 27 are included. Here, the control unit 11 uses the original image to be protected from tampering and a unique secret key as input data.

  The block dividing unit 21 divides the input original image into predetermined blocks such as 8 × 8 blocks, such as JPEG (Joint Photographic Experts Group).

  The frequency conversion unit 22 calculates a frequency conversion coefficient for each block image divided by the block division unit 21 by using, for example, discrete cosine transform (DCT (Discrete Cosine Transform) conversion). In this embodiment, the DCT transform is used as an example, but it is also possible to calculate the frequency transform coefficient using a discrete wavelet transform, a discrete Hadamard transform, or the like.

  FIG. 3 shows DCT transform coefficients as an example of frequency transform coefficients for compressed images. As shown in FIG. 3, 8 × 8 = 64 DCT coefficients obtained by dividing the vertical frequency component and the horizontal frequency component into predetermined frequency components are calculated by the frequency conversion unit 22. The frequency conversion unit 22 outputs the calculated frequency conversion coefficient to the quantization unit 23.

  The quantization unit 23 calculates a quantized DCT coefficient, which is an example of a quantized frequency conversion coefficient, using a quantization table corresponding to the compression rate. FIG. 4 shows a first quantization table as an example of the quantization table. As shown in FIG. 4, the first quantization table is set so that, for example, the coefficient of the higher-order frequency component that hardly affects the user visibility is increased.

FIG. 5 shows a quantized DCT coefficient as an example of a quantized frequency conversion coefficient. Note that the quantized DCT coefficient shown in FIG. 5 is a coefficient calculated using the first quantization table shown in FIG. Also, once quantized DCT coefficients are reversible with respect to the quantization processing using the same quantization table, and when the inverse quantization transform is executed, the DCT coefficients return to the basic frequency transform coefficients shown in FIG. Here, the quantization frequency conversion coefficient is calculated according to the following equation.
(Equation 1)
Sqvu = round (Svu / Quv)
Where Sqvu is the v (horizontal frequency component) row of the quantized frequency transform coefficient block, the quantized frequency transform coefficient of u (vertical frequency component) column,
Svu is the frequency conversion coefficient in the v row and u column of the frequency conversion coefficient block,
Quv is a coefficient of v rows and u columns of the quantization table (Qvu is a positive integer).

  As shown in FIG. 5, as the quantized frequency conversion coefficient becomes a high frequency component, the number of places where the coefficient becomes zero increases. Here, the following events were newly noticed by the present inventors. FIG. 6 shows a quantized DCT coefficient as an example of a quantized frequency transform coefficient quantized with an arbitrary quantization table different from the first quantization table for recompression. As shown in FIG. 6, when recompression is performed, it is confirmed that the quantized DCT coefficients are different. For this reason, if a hash value is simply generated from a quantized DCT coefficient, the above-described false detection of falsification occurs.

  Here, focusing on the position where the absolute value of the quantized DCT coefficient is 0, the value does not change even if the quantization frequency transform coefficient is calculated using an arbitrary quantization table for recompression. Remains. If this event is used, if a value other than 0 is taken at a position where the absolute value of the quantized DCT coefficient of the image to be tampered with is 0, it is determined that the image has been tampered with. It becomes possible to do.

  FIG. 7A shows the frequency conversion coefficient of the original image. FIG. 7B shows a quantized frequency transform coefficient obtained by transforming the frequency transform coefficient of FIG. 7A using the first quantization table. FIG. 7C shows a quantum in which the frequency conversion coefficient in FIG. 7A is converted using an arbitrary first quantization table other than the first quantization table, and a part of the coefficient is altered. The conversion frequency conversion coefficient is shown. As shown in FIGS. 7A to 7C, the falsification corresponding to the position of the quantized frequency transform coefficient block of 0 where the absolute value of the quantized frequency transform coefficient of the original original image is the minimum value. When the quantization frequency conversion coefficient of the compressed image to be detected has a value other than 0, it can be determined that the image has been tampered with. In addition, although the quantization frequency conversion coefficient is described as an example of the present embodiment, the same principle can be applied even if the frequency conversion coefficient is used. As shown in FIGS. 7A and 7C, the tampering detection target compression corresponding to the position of the frequency conversion coefficient block of 0 where the absolute value of the frequency conversion coefficient of the original original image is the minimum value. When the frequency conversion coefficient of the image takes a value other than 0, it can be determined that the image has been falsified.

  In addition, although the quantized DCT coefficient is mentioned as an example of the present embodiment, the same concept can be applied even when the quantized frequency transform coefficient such as the quantized Hadamard transform coefficient and the quantized wavelet transform coefficient is 0. .

Further, as an example of the present embodiment, the case where the quantization frequency conversion coefficient is 0 has been described as an example. However, it is possible to detect image falsification even with a value other than 0 by using the following equation.
(Equation 2)
Sqvu = round (Svu / Quv) + α (when Svu ≧ 0),
Sqvu = round (Svu / Quv) −α (when Svu <0),
Here, α is a predetermined integer.
When α is set to an arbitrary predetermined integer using the above formula, the value of α can be determined as a coefficient whose absolute value is the minimum value among the quantized frequency transform coefficients. In addition, when the value of α is determined as a coefficient whose absolute value is the minimum value among the frequency conversion coefficients, a numerical value that minimizes the coefficient in the frequency conversion coefficient block is determined, and α may be added to the numerical value. In the following description, the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value, and based on an arbitrary quantization table other than the first quantization table by compression such as recompression. A coefficient whose minimum value does not change even when the frequency conversion coefficient is quantized, that is, a coefficient whose minimum value does not change in the compression method is defined as a minimum invariant coefficient.

  2 scans the frequency transform coefficient block or the quantized frequency transform coefficient block in, for example, raster order, detects the position of the minimum invariant coefficient, and sends the position information of the minimum invariant coefficient to the generation unit 26. Output. When α is the minimum invariant coefficient in the frequency transform coefficient or the quantized frequency transform coefficient, the invariant coefficient position detection unit detects the position of the minimum invariant coefficient where the frequency transform coefficient or the quantized frequency transform coefficient is α. The position information of the minimum invariant coefficient is output to the generation unit 26.

  The generation unit 26 acquires the position information of the minimum invariant coefficient from the invariant coefficient position detection unit 25. For example, the frequency conversion coefficient or the quantization frequency is 0 when the frequency conversion coefficient or the quantization frequency conversion coefficient is the minimum invariance coefficient. A conversion coefficient that is not the minimum invariant coefficient is generated as a falsification detection code and output to the signature generation unit 27. At this time, the generation unit 26 can also add to the falsification detection code the position information of the minimum invariant coefficient or an identifier indicating whether the falsification detection code has been generated with either the frequency conversion coefficient or the quantized frequency conversion coefficient. . The position information of the minimum invariant coefficient added to the falsification detection code may be, for example, the serial number in the scan order, the coordinate value (v, u) of the frequency transform coefficient block, or the quantized frequency transform coefficient block.

  Further, the generation unit 26 can also generate the falsification detection code without acquiring the position information of the minimum invariant coefficient from the invariant coefficient position detection unit 25. Specifically, the generation unit 26 scans the frequency transform coefficient block or the quantized frequency transform coefficient block, for example, in raster order, and, for example, the frequency transform coefficient or the quantized frequency transform coefficient has a minimum invariant coefficient of 0, the frequency transform coefficient or When the quantized frequency conversion coefficient is not the minimum invariant coefficient, a code with 1 is generated as a falsification detection code.

  FIG. 8A is a conceptual diagram in which the position of the minimum invariant coefficient of the quantization frequency coefficient of the quantization frequency conversion coefficient block of the original original image is converted to α. FIG. 8B shows an example of a falsification detection code. As shown in FIGS. 8A and 8B, the invariant coefficient position detection unit 25 or the generation unit 26 scans the quantized frequency transform coefficient block, for example, in raster order, and then the quantized frequency transform coefficient is the minimum invariant coefficient. The falsification detection code is generated from the case where α is 0 and the quantization frequency conversion coefficient is 1 other than the minimum invariant coefficient α. When the position information of the minimum invariant coefficient is used, the position information of the minimum invariant coefficient α such as the coordinate value (v, u) of the quantization frequency transform coefficient block is added to the falsification detection code as necessary. 8 (a) and 8 (b) show an example using a quantized frequency transform coefficient block, but the same processing is performed even when a frequency transform coefficient block is used. Detailed description is omitted.

  The generation unit 26 represents the falsification detection code as 0 or 1 for each frequency conversion coefficient or each quantization frequency conversion coefficient, but information of a plurality of bits according to the size of the frequency conversion coefficient or the quantization frequency conversion coefficient. It may be expressed as Specifically, the generation unit 26 classifies coefficients other than the minimum invariant coefficient into a plurality of predetermined ranges, and generates a falsification detection code. FIG. 9 shows a correspondence table between the range of the quantization frequency conversion coefficient value and the falsification detection code. When the correspondence table of FIG. 9 is used, the position information of the quantized frequency transform coefficient belonging to each size category is output from the invariant position detection unit 25. In addition, since it becomes the same process also when a frequency conversion coefficient is used, detailed description is abbreviate | omitted.

  Here, FIG. 10 shows a conceptual diagram of the zigzag scanning method. FIG. 11 is a conceptual diagram of the vertical direction priority scan method. As shown in FIG. 10 or FIG. 11, in addition to the raster scan described above, the quantized frequency transform coefficient block can be scanned in a scan order such as a zigzag scan and a vertical priority scan. Note that the same processing is performed when the frequency conversion coefficient block is used, and thus detailed description thereof is omitted.

  The signature generation unit 27 encrypts the falsification detection code generated by the generation unit 26 using a unique private key that the image processing apparatus 10 has in advance, and outputs it as electronic signature data. The unique secret key is stored, for example, in the main storage unit 12 or the like. Furthermore, a public key that is a unique private key pair is also stored in, for example, the main storage unit 12 or the like. The signature generation unit 27 acquires a secret key from the main storage unit 12 or the like in advance. Further, the signature generation unit 27 may calculate a hash value using an existing hash function such as SHA-1, and finally encrypt the hash value using a secret key and output it as electronic signature data. Note that the signature generation unit 27 is not an essential component, and may be provided as necessary. When the signature generation unit 27 is not a constituent requirement, the generation unit 26 outputs a falsification detection code.

  The variable length encoding unit 24 compresses and encodes the quantization frequency transform coefficient acquired from the quantization unit 23 using a Huffman code or the like. The variable length encoding unit 24 outputs a compressed image that has been compression encoded.

  The image processing apparatus 10 outputs a compressed image, generated digital signature data or falsification detection code, and a public key that is a pair of a unique secret key. These pieces of information are used for subsequent alteration detection. Next, each process of the image processing apparatus functioning as a falsification preventing apparatus will be described in detail.

(Falsification prevention processing)
Next, the operation of the image processing apparatus 10 that functions as a falsification preventing apparatus according to the first embodiment will be described. FIG. 12 is a flowchart illustrating an example of falsification prevention processing according to the first embodiment.

  In step S1201 shown in FIG. 12, when an original image to be tampered with is input, the block dividing unit 21 divides the image into a plurality of blocks of 8 × 8 pixels, for example.

  In step S1202, the frequency conversion unit 22 performs frequency conversion on each image divided into a plurality of blocks, and calculates a frequency conversion coefficient.

  In step S1203, the quantization unit 23 calculates a quantization frequency transform coefficient using an arbitrary quantization table corresponding to the compression rate.

  In step S1204, the invariant coefficient position detection unit 25 determines that the position of the frequency transform coefficient in which the frequency transform coefficient is the minimum invariant coefficient in the frequency transform coefficient block or the quantized frequency transform coefficient in the quantized frequency transform coefficient block is the smallest. The position of the quantized frequency transform coefficient that becomes an invariant coefficient is detected. When the frequency conversion coefficient or the quantized frequency conversion coefficient is α, the minimum invariant coefficient is defined in advance. For example, it is assumed that the value of α is stored in the invariant coefficient position detection unit 25, for example.

  In step S1205, the generation unit 26 generates a falsification detection code based on the position information of the minimum invariant coefficient detected by the invariant coefficient position detection unit 25. Specifically, the generation unit 26 acquires the position information of the minimum invariant coefficient from the invariant coefficient position detection unit 25. For example, the frequency conversion coefficient or the quantized frequency conversion coefficient sets the minimum invariant coefficient to 0, the frequency conversion coefficient or the quantum A value obtained when the normalized frequency conversion coefficient is not the minimum invariant coefficient is generated as a falsification detection code and output to the signature generation unit 27. At this time, the generation unit 26 may add the position information of the minimum invariant coefficient to the falsification detection code. Note that the generation unit 26 may represent the falsification detection code as information of a plurality of bits according to the size of the frequency conversion coefficient or the quantization frequency conversion coefficient.

  In step S1206, the generation unit 26 determines whether the generation of the falsification detection code is completed for each image divided into a predetermined number of blocks. If not (step S1206-No), the process returns to step S1204. If completed (step S1206-Yes), the process proceeds to step S1207.

  In step S1207, the variable length encoding unit 24 encodes the quantized frequency transform coefficient calculated in step S1203 using, for example, a Huffman code.

  In step S1208, the signature generation unit 27 encrypts the falsification detection code generated in step S1205 with a secret key. Alternatively, the signature generation unit 27 may take a hash using a hash function.

  Note that the image processing apparatus 10 may execute the processing in step S1205 and the processing in step S1207 in parallel. Alternatively, the image processing apparatus 10 may execute the process of step S1205 before performing the process of step S1207.

  As described above, according to the first embodiment, the falsification detection code is generated based on the invariant coefficient whose value does not change even if recompression is performed (in other words, an arbitrary quantization table is used). In addition, it is possible to prevent erroneous detection.

(Example 2)
Next, the image processing apparatus 30 according to the second embodiment will be described. The image processing device 30 functions as a tampering detection device. The image processing apparatus 30 performs a common falsification detection process on the image output by the falsification preventing apparatus 1 of the first embodiment.

  FIG. 13 is a diagram illustrating an example of the configuration of the image processing apparatus 30. An image processing device 30 illustrated in FIG. 13 functions as the falsification detection device 2 that detects falsification of an image. An image processing apparatus 30 illustrated in FIG. 13 includes a control unit 31, a main storage unit 32, an auxiliary storage unit 33, a display control unit 34, a recording medium I / F unit 36, and an input I / F unit 38. Each unit is connected via a bus so that data can be transmitted / received to / from each other.

  The control unit 31 is a CPU (Central Processing Unit) that controls each device, calculates data, and processes in the computer. The control unit 31 is an arithmetic device that executes a program stored in the main storage unit 32 or the auxiliary storage unit 33. The control unit 31 receives data from each storage unit, calculates and processes the data, and then outputs the data to the output unit and each storage unit.

  For example, the control unit 31 plays a role of a falsification detection function for an image by executing a falsification detection program stored in the auxiliary storage unit 33.

  The main storage unit 32 is, for example, a RAM (Random Access Memory), and is a storage unit that stores or temporarily stores programs and data such as an OS and application software that are basic software executed by the control unit 31. The main storage unit 32 functions as a work memory for storing programs and data.

  The auxiliary storage unit 33 is, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and is a storage device that stores data related to application software. The auxiliary storage unit 33 stores a falsification detection program.

  The auxiliary storage unit 33 stores, for example, a compressed image, a public key, and an electronic signature acquired from the image processing apparatus 10 that functions as a falsification preventing apparatus. The auxiliary storage unit 33 may store an image acquired from the recording medium 37 or the like.

  The display control unit 34 performs display control in order to display images and data on the display unit 35.

  The recording medium I / F (interface) unit 36 is an interface between the image processing apparatus 30 and a recording medium 37 (for example, a flash memory) connected via a data transmission path such as a USB (Universal Serial Bus).

  A predetermined program (an image processing program that functions as a falsification detection program) is stored in the recording medium 37, and the program stored in the recording medium 37 is stored in the image processing apparatus 30 via the recording medium I / F unit 36. To be installed. The installed predetermined program can be executed by the image processing apparatus 30.

  If the recording medium 37 is an SD card, for example, the recording medium I / F unit 36 is an SD card slot.

  The input I / F unit 38 acquires data input from a mouse / keyboard 39 serving as an input device. The acquired data is stored in the main storage unit 32 or the auxiliary storage unit 33. Note that the mouse / keyboard 39 and the display unit 35 may be built in the image processing apparatus 30.

  Further, the image processing apparatus 30 includes a communication unit, and performs wired or wireless communication. The communication unit receives, for example, a compressed image, a public key, and an electronic signature from the image processing apparatus 10 that functions as a falsification preventing apparatus.

(Falsification detection function)
Next, the control unit 31 having a falsification detection function will be described in detail. FIG. 14 is a functional block diagram illustrating an example of the control unit 31 according to the second embodiment. The control unit 31 illustrated in FIG. 14 includes a variable length decoding unit 41, an inverse quantization unit 42, an inverse frequency conversion unit 43, a block combination unit 44, an invariant coefficient position detection unit 45, a generation unit 46, a signature authentication unit 47, a comparison unit. 48. Here, the control unit 31 uses, as input data, a compressed image to be detected for falsification, a digital signature, and a public key that is paired with the private key of the image processing apparatus 10.

  The variable length decoding unit 41 acquires a compressed image, decodes the quantized frequency transform coefficient encoded by Huffman code or the like, and outputs the decoded image to the inverse quantization unit 42 and the invariant coefficient position detection unit 45. Note that the quantized frequency transform coefficient decoded by the variable length decoding unit 41 is, for example, the quantized frequency transform coefficient illustrated in FIG.

  The inverse quantum unit 42 converts the decoded quantized frequency transform coefficient into a frequency transform coefficient using the quantization table, and outputs the frequency transform coefficient to the inverse frequency transform unit 43 and the invariant coefficient position detection unit 45. As the quantization table, for example, the first quantization table shown in FIG. 4 may be used. The frequency transform coefficient inversely quantized by the inverse quantum unit 42 becomes, for example, the frequency transform coefficient shown in FIG. In addition, the inverse quantization unit 42 may store a plurality of quantization tables, and the quantization table used for the frequency conversion coefficient may be designated from the image processing apparatus 10. Further, the quantization table used for the frequency conversion coefficient may be acquired from the image processing apparatus 10.

  The inverse frequency conversion unit 43 performs inverse frequency conversion on the frequency conversion coefficient, converts the frequency conversion coefficient into an image divided into predetermined blocks (for example, a plurality of blocks of 8 × 8 pixels), and outputs the image to the block combination unit 44. . For the inverse frequency transform, for example, an inversely spaced cosine transform (IDCT), an inverse wavelet transform, an inverse discrete Hadamard transform, or the like can be used.

  The block combining unit 44 combines the images divided into predetermined blocks and outputs the original image. The output original image is displayed on the display unit 35, for example.

The invariant coefficient position detection unit 45 scans the frequency transform coefficient block or the quantized frequency transform coefficient block, for example, in raster order, detects the position of the minimum invariant coefficient, and outputs the position information of the minimum invariant coefficient to the generation unit 46. The function of the invariant coefficient position detection unit 45 has the same function as the invariant coefficient position detection unit 25 of FIG. When the frequency conversion coefficient or the quantized frequency conversion coefficient is α as the minimum invariant coefficient, the value of α is the value of α used in advance by the invariant coefficient position detection unit 25 in FIG. It can be set in the unit 45 or acquired from the image processing apparatus 10.
Note that the invariant coefficient position detection unit 45 includes a selector (not shown) and can select whether to acquire a frequency conversion coefficient or a quantization frequency conversion coefficient based on an identifier or the like.

  The generation unit 46 acquires the position information of the minimum invariant coefficient from the invariant coefficient position detection unit 45, and sets the coefficient whose frequency conversion coefficient or quantized frequency conversion coefficient is the minimum invariant coefficient to 0, the frequency conversion coefficient or the quantized frequency conversion coefficient. Is generated as a falsification detection code, and is output to the comparison unit 48. The function of the generation unit 46 is the same as that of the generation unit 26 in FIG. Further, the generation unit 46 stores a correspondence table of the quantization frequency conversion coefficient value range and the falsification detection code shown in FIG. 9 in advance or obtains them from the image processing apparatus 10 to obtain the quantization frequency conversion. It is possible to express with multiple bits of information according to the coefficient size. Although FIG. 9 shows an example of the so-called quantized frequency transform coefficient, detailed description is omitted for the same processing even when the frequency transform coefficient is used.

  The signature authenticating unit 47 acquires from the image processing apparatus 10 a public key that is paired with a secret key obtained by encrypting the falsification detection code generated by the generating unit 26 of the image processing apparatus 10 and an electronic signature. The signature authentication unit 47 confirms the electronic signature using the public key, decrypts the encrypted falsification detection code, and outputs it to the comparison unit 48. When the image processing apparatus 10 does not encrypt the falsification detection code, the signature authentication unit 47 acquires the plaintext falsification detection code from the image processing apparatus 10 and outputs it to the comparison unit 48. The confirmation result of the electronic signature is displayed on the display unit 35, for example.

  Here, for convenience of explanation, the falsification detection code generated by the generation unit 46 of the image processing device 30 is defined as the first falsification detection code, and the falsification detection code generated by the generation unit 26 of the image processing device 10 is defined as the second falsification detection code. It shall be defined as a code.

The comparison unit 48 compares the first tampering detection code and the second tampering detection code, and the coefficients that are the least invariant coefficients in the second tampering detection code are all the minimum invariants in the first tampering detection code. If it is a coefficient, it is determined that there is no falsification, and if the coefficient that was the least invariant coefficient in the second falsification detection code is not the minimum invariant coefficient in the first falsification detection code, it is determined that there is falsification, and the falsification verification result is output To do.
For example, the comparison unit 48
First alteration detection code = 11100011, 10011000, 10,.
Second alteration detection code = 11100011, 10011000, 10,.
In this case, since all the coefficients that were the minimum invariant coefficients in the second falsification detection code are the minimum invariant coefficients in the first falsification detection code, it is determined that there is no falsification.
The comparison unit 48
First alteration detection code = 11101111, 10011010, 10...
Second alteration detection code = 11100011, 10011000, 10,.
In this case, since the coefficient that was the minimum invariant coefficient in the second falsification detection code is a coefficient that is not the minimum invariant coefficient in the first falsification detection code, it is determined that there is falsification.
The falsification verification result is displayed on the display unit 35, for example.

  If the comparison unit 48 determines that there is a coefficient that is the minimum invariant coefficient in the second falsification detection code and that is not the minimum invariant coefficient in the first falsification detection code, and determines that there is falsification, the comparison unit 48 The block including the coefficient that is the minimum invariant coefficient in the first falsification detection code and the coefficient that is not the minimum invariant coefficient is detected, and the position information of the minimum invariant coefficient included in the falsification detection code is output to the block combination unit 44.

  The block combining unit 44 superimposes and outputs an arbitrary mark such as a circle at the position where the falsification is performed on the original image based on the position information of the falsified block. The original image on which an arbitrary mark is superimposed is displayed on the display unit 35, for example.

(Falsification detection process 1)
Next, the operation of the image processing device 30 functioning as a tamper detection device in the second embodiment will be described. FIG. 15 is a flowchart (part 1) illustrating an example of falsification detection processing according to the second embodiment. FIG. 16 is a flowchart (part 2) illustrating an example of falsification detection processing according to the second embodiment. The processing illustrated in FIGS. 15 and 16 is processing for detecting falsification by inputting the electronic signature, the public key, and the compressed image to be tampered with detected in the first embodiment.

  In step S1501, the variable length decoding unit 41 acquires a compressed image divided into a predetermined number of blocks, decodes a quantized frequency transform coefficient encoded by a Huffman code or the like, and an inverse quantization unit 42; Output to the invariant coefficient position detection unit 45.

  In step S1502, the inverse quantum unit 42 converts the decoded quantized frequency transform coefficient into a frequency transform coefficient using the quantization table and outputs the frequency transform coefficient to the inverse frequency transform unit 43 and the invariant coefficient position detection unit 45.

  In step S1503, the inverse frequency conversion unit 43 performs inverse frequency conversion on the frequency conversion coefficient, converts the frequency conversion coefficient into an image divided into predetermined blocks (for example, a plurality of blocks of 8 × 8 pixels), and a block combination unit 44.

  In step S1504, the block combining unit 44 combines the images divided into predetermined blocks and outputs the original image.

  In step S1505, the invariant coefficient position detection unit 45 scans the frequency transform coefficient block or the quantized frequency transform coefficient block, for example, in raster order, detects the position of the minimum invariant coefficient, and generates the position information of the minimum invariant coefficient. Output to. The process in step S1505 is the same as that in step S1204 in FIG.

  In step S1506, the generation unit 46 acquires the position information of the minimum invariant coefficient, the frequency transform coefficient or the quantized frequency transform coefficient is 0, and the frequency transform coefficient or the quantized frequency transform coefficient is other than the minimum invariant coefficient. A coefficient with a coefficient of 1 is generated as the first falsification detection code and output to the comparison unit 48. Note that step S1506 is the same as step 1205 in FIG.

  In step S1507, the generation unit 46 determines whether generation of the falsification detection code is completed for each compressed image divided into a predetermined number of blocks. If not (step S1507-No), the process returns to step S1505. If completed (step S1507-Yes), the process proceeds to step S1509.

  In step S1508, the signature authentication unit 47 confirms the electronic signature using the public key, decrypts the second falsification detection code generated by the generation unit 26 of the encrypted image processing apparatus 10, and compares the comparison unit 48. Output to.

  In step S1509, the comparison unit 48 compares the first tampering detection code and the second tampering detection code, and determines that there is no tampering if they match (step S1510-No), and if there is no matching, it indicates that tampering has occurred. Judgment is made (step S1510-Yes), and the falsification verification result is output to the display unit 35, respectively. (Steps S1511, S1512)

  In step S1513, if the block combining unit 44 determines that there is a coefficient that is the minimum invariant coefficient in the second falsification detection code and that is not the minimum invariant coefficient in the first falsification detection code, and if there is a falsification, The position information of the block including the coefficient that is the smallest invariant coefficient in the second alteration detection code and the coefficient that is not the smallest invariant coefficient in the first alteration detection code is acquired from the comparison unit 48. Further, the block combining unit 44 superimposes and outputs an arbitrary mark such as a round mark on the original image based on the position information of the falsified block.

  As described above, according to the second embodiment, it is possible to prevent false detection of falsification of an image that has not been falsified and has only been recompressed. In addition, when there is tampering such as rewriting an image, the position can be specified in units of blocks.

(Modification of the falsification detection function)
Next, a modified example of the control unit 31 having a falsification detection function will be described in detail. FIG. 17 is a functional block diagram illustrating an example of the control unit 31 according to the third embodiment. The control unit 31 illustrated in FIG. 17 includes a variable length decoding unit 41, an inverse quantization unit 42, an inverse frequency conversion unit 43, a block combination unit 44, a signature authentication unit 47, and a determination unit 51. Here, the control unit 31 uses, as input data, a compressed image to be detected for falsification, a digital signature, and a public key that is paired with the private key of the image processing apparatus 10.

  Since the variable length decoding unit 41, the inverse quantization unit 42, the inverse frequency conversion unit 43, the block combination unit 44, and the signature authentication unit 47, excluding the determination unit 51, are the same as the functions shown in FIG. Omitted.

  The determination unit 51 acquires the falsification detection code decrypted from the signature authentication unit 47. Further, the determination unit 51 acquires the position information of the minimum invariant coefficient included in the falsification detection code acquired from the signature authentication unit 47. Further, the determination unit 51 acquires the quantized frequency transform coefficient from the variable length decoding unit 41 or the frequency transform coefficient from the inverse quantization unit 42. The determination unit 51 includes a selector (not shown) and can select whether to acquire a frequency conversion coefficient or a quantization frequency conversion coefficient based on an identifier or the like.

The determination unit 51 determines the presence / absence of falsification based on the frequency conversion coefficient or the quantized frequency conversion coefficient of the falsification detection target image corresponding to the position information of the minimum invariant coefficient included in the falsification detection code. Specifically, if the frequency conversion coefficient or quantized frequency conversion coefficient of the falsification detection target image corresponding to the position information of the minimum invariant coefficient included in the falsification detection code is a coefficient other than the minimum invariant coefficient, falsification is present. Is determined.
When the frequency conversion coefficient or the quantized frequency conversion coefficient is α as the minimum invariant coefficient, the value of α is previously set to the determination unit 51 by using the value of α used by the invariant coefficient position detection unit 25 in FIG. It can be set or acquired from the image processing apparatus 10. Further, when the determination unit 51 determines that there is falsification, the determination unit 51 outputs the position information of the minimum invariant coefficient to the block combination unit 44.

  A specific example will be described with reference to FIGS. The determination unit 51 acquires coordinate information of the minimum invariant coefficient from the coordinate value of the quantized frequency transform coefficient block, which is an example of the position information of the minimum invariant coefficient included in the falsification detection code of FIG. Taking FIG. 8B as an example, the coordinate information is (1, 4), (1, 5). Next, the determination unit 51 uses the coordinate values (1, 4), (1, 5) of the quantization frequency transform coefficient block of the falsification detection target image in FIG. )..,... Are referred to, it is determined that there is no tampering if all of the coefficients are minimum invariant coefficients, and it is determined that tampering exists if at least one of the coefficients is other than the minimum invariant coefficient. Further, although the quantized frequency transform coefficient block is described as an example, detailed description is omitted because the same processing is performed even when the frequency transform block is used.

(Modification of falsification detection processing)
Next, the operation of the image processing apparatus 30 functioning as a falsification detection apparatus in the third embodiment will be described. FIG. 18 is a flowchart illustrating an example of falsification detection processing according to the third embodiment. The process illustrated in FIG. 18 is a process for detecting falsification by inputting the digital signature, the public key, and the compressed image to be falsified to be detected in the first embodiment.

  The processing of steps S1601 to S1605 and S1607 to S1610 is the same as the processing of steps S1501 to S1504, S1508, and S1510 to 1513 shown in FIGS.

  In step S1606, the determination unit 51 determines the presence / absence of falsification based on the frequency conversion coefficient or the quantized frequency conversion coefficient corresponding to the position information of the minimum invariant coefficient. Specifically, if the frequency conversion coefficient or quantized frequency conversion coefficient of the falsification detection target image corresponding to the position information of the minimum invariant coefficient included in the falsification detection code is a coefficient other than the minimum invariant coefficient, falsification is present. Is determined. If the determination unit 51 determines that there has been tampering, the determination unit 51 outputs the position information of the minimum invariant coefficient to the block combination unit 44.

  As described above, according to the third embodiment, it is possible to prevent false detection of falsification of an image that has not been falsified and has only been recompressed. In addition, when there is tampering such as rewriting an image, the position can be specified in units of blocks. Furthermore, it is not necessary to create a falsification detection code, and the processing speed of falsification detection can be improved.

(Modification of the falsification prevention function)
Next, a modified example of the control unit 11 having a falsification preventing function will be described in detail. FIG. 19 is a functional block diagram illustrating an example of the control unit 11 according to the fourth embodiment. The control unit 11 illustrated in FIG. 19 includes a variable length decoding unit 41, an inverse quantization unit 42, an invariant coefficient position detection unit 25, a generation unit 26, and a signature generation unit 27. Here, the control unit 11 uses, as input data, a compressed image including a quantized frequency conversion coefficient to be tampered with and a unique secret key.

  Since the variable length decoding unit 41, the inverse quantization unit 42, the invariant coefficient position detection unit 25, the generation unit 26, and the signature generation unit 27 are the same as the functions shown in FIGS. Omitted.

  The variable length decoding unit 41 acquires a compressed image, decodes the quantized frequency transform coefficient encoded by Huffman code or the like, and outputs the decoded image to the inverse quantization unit 42 and the invariant coefficient position detection unit 45.

  The inverse quantum unit 42 converts the decoded quantized frequency transform coefficient into a frequency transform coefficient using the quantization table, and outputs the frequency transform coefficient to the invariant coefficient position detecting unit 45. In addition, when the falsification detection code is not generated based on the frequency conversion coefficient, the inverse quantization unit 42 is not an essential configuration.

  The invariant coefficient position detection unit 25 scans the frequency transform coefficient block or the quantized frequency transform coefficient block, for example, in raster order, detects the position of the minimum invariant coefficient, and outputs the position information of the minimum invariant coefficient to the generation unit 26. When the frequency conversion coefficient or the quantized frequency conversion coefficient is α as the minimum invariant coefficient, the invariant coefficient position detection unit detects the position of the minimum invariant coefficient whose quantity frequency conversion coefficient or child frequency conversion coefficient is α. And the position information of the minimum invariant coefficient is output to the generation unit 26.

The generation unit 26 acquires the position information of the minimum invariant coefficient from the invariant coefficient position detection unit 25. For example, the frequency conversion coefficient or the quantization frequency is 0 when the frequency conversion coefficient or the quantization frequency conversion coefficient is the minimum invariance coefficient. A conversion coefficient that is not the minimum invariant coefficient is generated as a falsification detection code and output to the signature generation unit 27. At this time, the generation unit 26 can also add to the falsification detection code the position information of the minimum invariant coefficient or an identifier indicating whether the falsification detection code has been generated with either the frequency conversion coefficient or the quantized frequency conversion coefficient. . The position information of the minimum invariant coefficient added to the falsification detection code is, for example,
Any serial number in the scan order or coordinate values (v, u) of the frequency transform coefficient block or quantized frequency transform coefficient block may be used.

  The signature generation unit 27 encrypts the falsification detection code generated by the generation unit 26 using a unique private key that the image processing apparatus 10 has in advance, and outputs it as electronic signature data. The unique secret key is stored, for example, in the main storage unit 12 or the like. Note that the signature generation unit 27 is not an essential component, and may be provided as necessary. When the signature generation unit 27 is not a constituent requirement, the generation unit 26 outputs a falsification detection code.

  As described above, according to the fourth embodiment, it is possible to generate a falsification detection code for a compressed image, and it is possible to prevent erroneous detection.

  In addition, recording the program for realizing the falsification prevention process and the falsification detection process described in each embodiment described above on a recording medium causes the computer to perform the falsification prevention process and the falsification detection process in each embodiment. Can do. For example, it is possible to record the program on a recording medium and cause the computer or portable device to read the recording medium on which the program is recorded, thereby realizing the above-described falsification prevention processing and falsification detection processing.

  The recording medium is a recording medium that records information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, or a magneto-optical disk, or a semiconductor that electrically records information, such as a ROM or flash memory. Various types of recording media such as a memory can be used.

  The program executed by the image processing apparatus has a module configuration including each unit described in each embodiment. As actual hardware, when the control unit reads out and executes a program from the auxiliary storage unit, one or more of the above-described units are loaded on the main storage unit, and one or more of the units are on the main storage unit. To be generated.

  The image to be tampered with or tampered with may be a moving image, and the above processing may be performed for each frame, or the above processing may be performed for each frame at a predetermined interval.

  In the above-described embodiments, each component of each illustrated device does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  All examples and specific terms listed herein are intended for instructional purposes to help the reader understand the concepts contributed by the inventor to the present invention and the promotion of the technology. It should be construed that it is not limited to the construction of any example herein, such specific examples and conditions, with respect to showing the superiority and inferiority of the present invention. While embodiments of the present invention have been described in detail, it should be understood that various changes, substitutions and modifications can be made thereto without departing from the scope of the invention.

The following supplementary notes are further disclosed regarding the embodiment described above and its modifications.
(Appendix 1)
A frequency conversion unit for converting an image into a frequency conversion coefficient;
A quantization unit that quantizes the frequency transform coefficient based on a first quantization table to calculate a quantized frequency transform coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table A generation unit that generates a falsification detection code that detects falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
An image processing apparatus comprising:
(Appendix 2)
The generating unit generates the falsification detection code by distinguishing the minimum invariant coefficient from the frequency conversion coefficient or the quantized frequency conversion coefficient and a coefficient other than the minimum invariant coefficient. The image processing apparatus described.
(Appendix 3)
The position of the minimum invariant coefficient with respect to the quantized frequency transform coefficient block in which the quantized frequency transform coefficient is stored for each predetermined frequency component, or the frequency transform coefficient block in which the frequency transform coefficient is stored for each predetermined frequency component An invariant coefficient position detection unit for detecting the position of the minimum invariant coefficient;
The image processing apparatus according to appendix 1 or appendix 2, wherein the generation unit generates the falsification detection code based on position information of the minimum invariant coefficient.
(Appendix 4)
The image according to any one of supplementary notes 1 to 3, wherein the generation unit classifies coefficients other than the minimum invariant coefficient into a plurality of predetermined ranges and generates the falsification detection code. Processing equipment.
(Appendix 5)
The image processing apparatus according to any one of appendices 1 to 4, further comprising a signature generation unit that encrypts the falsification detection code with a secret key to generate an electronic signature.
(Appendix 6)
A block dividing unit for dividing the image into a predetermined number of blocks;
6. The image processing apparatus according to claim 1, wherein the frequency conversion unit converts each image divided into the predetermined number of blocks into the frequency conversion coefficient.
(Appendix 7)
An image is converted into a frequency conversion coefficient, the frequency conversion coefficient is quantized based on a first quantization table, and a quantized frequency conversion coefficient is obtained, and the absolute frequency of the frequency conversion coefficient or the quantized frequency conversion coefficient is obtained. Even if the value is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table, the minimum invariance defined by a coefficient that does not change the minimum value. A generator for generating a first falsification detection code for detecting falsification based on a coefficient;
A second falsification detection code generated based on the minimum invariant coefficient, and a comparison unit that compares the first falsification detection code and the second falsification detection code;
An image processing apparatus comprising:
(Appendix 8)
The second tampering detection code is generated by distinguishing the minimum invariant coefficient from the frequency conversion coefficient or the quantized frequency conversion coefficient and a coefficient other than the minimum invariant coefficient,
The generating unit generates the first falsification detection code by distinguishing the minimum invariant coefficient and a coefficient other than the minimum invariant coefficient from the frequency transform coefficient or the quantized frequency transform coefficient. The image processing apparatus according to appendix 7.
(Appendix 9)
The second tampering detection code is a quantized frequency transform coefficient block in which the quantized frequency transform coefficient is stored for each predetermined frequency component, or a frequency transform coefficient in which the frequency transform coefficient is stored for each predetermined frequency component. Generated based on the position information of the minimum invariant coefficient with respect to the block;
An invariant coefficient position detector that detects a position of the minimum invariant coefficient with respect to the quantized frequency transform coefficient block or the frequency transform coefficient block;
The generation unit generates the first falsification detection code based on position information of the minimum invariant coefficient detected by the invariant coefficient position detection unit.
The image processing apparatus according to appendix 7 or appendix 8, wherein
(Appendix 10)
An inverse quantization unit that converts the quantized frequency transform coefficient into the frequency transform coefficient;
An inverse frequency transform unit for transforming the frequency transform coefficient into an image divided into predetermined blocks;
A block combining unit that combines the images divided into the predetermined blocks and outputs an original image;
Further comprising
If the comparison unit detects falsification based on the comparison result between the first falsification detection code and the second falsification detection code, the comparison unit outputs position information of the falsified block to the block combination unit,
The block combining unit outputs a position where the falsified position is superimposed on the original image based on the position information.
The image processing apparatus according to appendix 9, wherein
(Appendix 11)
An electronic signature generated by encrypting the falsification detection code with a private key and a public key that is paired with the private key are obtained, and further includes a signature authentication unit that decrypts the electronic signature with the public key. The image processing apparatus according to any one of Appendix 7 to Appendix 10.
(Appendix 12)
An image is converted into a frequency conversion coefficient, and the frequency conversion coefficient is quantized based on a first quantization table;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table Obtaining a falsification detection code including position information of a minimum invariant coefficient defined by a coefficient whose minimum value does not change,
A determination unit that determines the presence or absence of falsification based on the frequency conversion coefficient or the quantized frequency conversion coefficient corresponding to the position information of the minimum invariant coefficient;
An image processing apparatus comprising:
(Appendix 13)
Convert the image to frequency conversion coefficient,
Quantizing the frequency transform coefficient based on a first quantization table to calculate a quantized frequency transform coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table Generating a falsification detection code for detecting falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
An image processing method in which processing is executed by a computer.
(Appendix 14)
A position of the minimum invariant coefficient with respect to a quantized frequency transform coefficient block in which the quantized frequency transform coefficient is stored for each predetermined frequency component or a frequency transform coefficient block in which the frequency transform coefficient is stored for each predetermined frequency component. Detect
14. The image processing method according to claim 13, wherein the generation includes generating the falsification detection code based on position information of the minimum invariant coefficient.
(Appendix 15)
An image is converted into a frequency conversion coefficient, and the frequency conversion coefficient is quantized based on a first quantization table to obtain a quantized frequency conversion coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table Generating a first falsification detection code for detecting falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
Obtaining a second tampering detection code generated based on the minimum invariant coefficient, and comparing the first tampering detection code and the second tampering detection code;
An image processing method in which processing is executed by a computer.
(Appendix 16)
The second tampering detection code is a quantized frequency transform coefficient block in which the quantized frequency transform coefficient is stored for each predetermined frequency component, or a frequency transform coefficient in which the frequency transform coefficient is stored for each predetermined frequency component. Generated based on the position information of the minimum invariant coefficient with respect to the block;
Detecting the position of the minimum invariant coefficient relative to the quantized frequency transform coefficient block or the frequency transform coefficient block;
The generating generates the first falsification detection code based on position information of the minimum invariant coefficient.
The image processing method according to appendix 15, wherein the computer executes the processing.
(Appendix 17)
Dequantizing the quantized frequency transform coefficient into the frequency transform coefficient;
The frequency transform coefficient is inverse frequency transformed into an image divided into predetermined blocks,
The original image is output by combining the images divided into the predetermined blocks,
The comparison is based on a comparison result between the first tampering detection code and the second tampering detection code, and when tampering is detected, outputs position information of the tampered block,
The output of the original image is to superimpose and output the altered block position on the original image based on the position information.
The image processing apparatus according to appendix 17, characterized by the above.
(Appendix 18)
Convert the image to frequency conversion coefficient,
Quantizing the frequency transform coefficient based on a first quantization table to calculate a quantized frequency transform coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table Generating a falsification detection code for detecting falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
An image processing program for causing a computer to execute processing.
(Appendix 19)
An image is converted into a frequency conversion coefficient, and the frequency conversion coefficient is quantized based on a first quantization table to obtain a quantized frequency conversion coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table Generating a first falsification detection code for detecting falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
Obtaining a second tampering detection code generated based on the minimum invariant coefficient, and comparing the first tampering detection code and the second tampering detection code;
An image processing program for causing a computer to execute processing.
(Appendix 20)
A variable length decoding unit that obtains a compressed image including a quantized frequency transform coefficient obtained by transforming an image into a frequency transform coefficient, and the frequency transform coefficient is quantized based on a first quantization table;
An inverse quantization unit that converts the quantized frequency transform coefficient into the frequency transform coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table A generation unit that generates a falsification detection code that detects falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
An image processing apparatus comprising:

Block division unit 21
Frequency converter 22
Quantization unit 23
Variable length encoding unit 24
Invariant coefficient position detector 25
Generator 26
Signature generator 27
Variable length decoding unit 41
Inverse quantization unit 42
Inverse frequency converter 43
Block coupling part 44
Invariant coefficient position detector 45
Generation unit 46
Comparison unit 48
Determination unit 51

Claims (9)

A frequency conversion unit for converting an image into a frequency conversion coefficient;
A quantization unit that quantizes the frequency transform coefficient based on a first quantization table to calculate a quantized frequency transform coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table A generation unit that generates a falsification detection code that detects falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
An image processing apparatus comprising:   The generation unit generates the falsification detection code by distinguishing the minimum invariant coefficient and a coefficient other than the minimum invariant coefficient from the frequency conversion coefficient or the quantized frequency conversion coefficient. The image processing apparatus according to 1. The position of the minimum invariant coefficient with respect to the quantized frequency transform coefficient block in which the quantized frequency transform coefficient is stored for each predetermined frequency component, or the frequency transform coefficient block in which the frequency transform coefficient is stored for each predetermined frequency component An invariant coefficient position detection unit for detecting the position of the minimum invariant coefficient;
The image processing apparatus according to claim 1, wherein the generation unit generates the falsification detection code based on position information of the minimum invariant coefficient. An image is converted into a frequency conversion coefficient, the frequency conversion coefficient is quantized based on a first quantization table, and a quantized frequency conversion coefficient is obtained, and the absolute frequency of the frequency conversion coefficient or the quantized frequency conversion coefficient is obtained. Even if the value is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table, the minimum invariance defined by a coefficient that does not change the minimum value. A generator for generating a first falsification detection code for detecting falsification based on a coefficient;
A second falsification detection code generated based on the minimum invariant coefficient, and a comparison unit that compares the first falsification detection code and the second falsification detection code;
An image processing apparatus comprising: The second tampering detection code is generated by distinguishing the minimum invariant coefficient from the frequency conversion coefficient or the quantized frequency conversion coefficient and a coefficient other than the minimum invariant coefficient,
The generating unit generates the first falsification detection code by distinguishing the minimum invariant coefficient and a coefficient other than the minimum invariant coefficient from the frequency transform coefficient or the quantized frequency transform coefficient. The image processing apparatus according to claim 4. The second tampering detection code is a quantized frequency transform coefficient block in which the quantized frequency transform coefficient is stored for each predetermined frequency component, or a frequency transform coefficient in which the frequency transform coefficient is stored for each predetermined frequency component. Generated based on the position information of the minimum invariant coefficient with respect to the block;
An invariant coefficient position detector that detects a position of the minimum invariant coefficient with respect to the quantized frequency transform coefficient block or the frequency transform coefficient block;
The generation unit generates the first falsification detection code based on position information of the minimum invariant coefficient detected by the invariant coefficient position detection unit.
The image processing apparatus according to claim 4, wherein the image processing apparatus is an image processing apparatus. An inverse quantization unit that converts the quantized frequency transform coefficient into the frequency transform coefficient;
An inverse frequency transform unit for transforming the frequency transform coefficient into an image divided into predetermined blocks;
A block combining unit that combines the images divided into the predetermined blocks and outputs an original image;
Further comprising
When the comparison unit detects falsification based on a comparison result between the first falsification detection code and the second falsification detection code, the comparison unit outputs position information of the falsified minimum invariant coefficient to the block combination unit. And
The block combining unit outputs a position where the falsified position is superimposed on the original image based on the position information.
The image processing apparatus according to claim 6. Convert the image to frequency conversion coefficient,
Quantizing the frequency transform coefficient based on a first quantization table to calculate a quantized frequency transform coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table Generating a falsification detection code for detecting falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
An image processing method in which processing is executed by a computer. An image is converted into a frequency conversion coefficient, and the frequency conversion coefficient is quantized based on a first quantization table to obtain a quantized frequency conversion coefficient;
Even when the absolute value of the frequency transform coefficient or the quantized frequency transform coefficient is the minimum value and the frequency transform coefficient is quantized based on an arbitrary quantization table other than the first quantization table Generating a first falsification detection code for detecting falsification based on a minimum invariant coefficient defined by a coefficient that does not change the minimum value;
Obtaining a second tampering detection code generated based on the minimum invariant coefficient, and comparing the first tampering detection code and the second tampering detection code;
An image processing method in which processing is executed by a computer.

Images