CN113344833B - Image enhancement method and device, electronic equipment and storage medium - Google Patents
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- 210000003462 vein Anatomy 0.000 claims abstract description 40
- 238000012545 processing Methods 0.000 claims abstract description 38
- 238000004364 calculation method Methods 0.000 claims description 13
- 238000010606 normalization Methods 0.000 claims description 8
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- 101100149954 Salmonella typhimurium (strain LT2 / SGSC1412 / ATCC 700720) spaM gene Proteins 0.000 description 14
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- 229940060587 alpha e Drugs 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/50—Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
Abstract
The application provides an image enhancement method, an image enhancement device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object; integrating the reversed phase image to obtain an integrated image corresponding to the reversed phase image; calculating according to the integral image to obtain an adaptive threshold corresponding to each pixel point in the image to be processed; and obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold. According to the embodiment of the application, the integral processing is carried out on the reverse phase image, the self-adaptive threshold value of each pixel point in the image to be processed is calculated, the enhanced image of the image to be processed is obtained according to the self-adaptive threshold value and the reverse phase image, and the definition of the finger veins in the image to be processed is improved through the enhancement of the image to be processed.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an image enhancement method, an image enhancement device, an electronic device, and a storage medium.
Background
The finger vein image is the same as the fingerprint and iris of the person, and the finger vein image of each person is different, so that the identity of the person can be identified through the finger veins. If an identity is to be recognized accurately, it is necessary to obtain a clear finger vein.
In the prior art, clear finger veins are obtained through finger vein image enhancement technology. The conventional method is to denoise the background shadow in the finger vein image, design and process the image by using a filter check, and eliminate the shadow noise in the finger pattern by a preset filter kernel with the capability of processing the shadow region, thereby achieving the purpose of highlighting the finger vein feature. There are commonly known Bilatial filter kernels, gabor filters, schmid filters, etc. The disadvantage of such methods is that the filter kernel is often of a fixed size, there is a certain incompatibility for different patterns, and the shadow cannot be completely distinguished from the finger vein feature points, so that the finger vein feature points are missing to a certain extent. However, since the size of the filtering kernel of the image is a fixed value, the filtering kernel cannot be adapted to the finger vein images with differences obtained under different instruments, so that the erroneous recognition of the finger vein region and shadow noise is caused, and the obtained finger vein images have low definition.
Disclosure of Invention
The embodiment of the application aims to provide an image enhancement method, an image enhancement device, electronic equipment and a storage medium, which are used for improving definition of a finger vein image.
In a first aspect, an embodiment of the present application provides an image enhancement method, including: acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object; integrating the reversed phase image to obtain an integrated image corresponding to the reversed phase image; calculating according to the integral image to obtain an adaptive threshold corresponding to each pixel point in the image to be processed; and obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold.
According to the embodiment of the application, the integral processing is carried out on the reverse phase image, the self-adaptive threshold value of each pixel point in the image to be processed is calculated, the enhanced image of the image to be processed is obtained according to the self-adaptive threshold value and the reverse phase image, and the definition of the finger veins in the image to be processed is improved through the enhancement of the image to be processed.
Further, the integrating processing is performed on the inverted image to obtain an integrated image corresponding to the inverted image, including: according to the formula IntI i,j ＝invI i,j +IntI i-1,j +IntI i,j-1 -IntI i-1,j-1 Calculating the value of each pixel point in the inverse image in an integral image to obtain the integral image; wherein: intI i,j The value of the pixel point in the ith row and the jth column in the integral image; invI i,j The gray value corresponding to the ith row and the jth column of pixel points in the inverted image is obtained; intI i-1,j The value of the pixel point corresponding to the j-th row of the i-1 row in the integral image is obtained; intI i,j-1 The value of the pixel point of the j-1 th row in the integral image; intI i-1,j-1 The value of the pixel point of the j-1 th row and the j-1 th column in the integral image.
According to the embodiment of the application, the integral image is obtained by carrying out integral processing on the reversed phase image, so that the time complexity of subsequent calculation can be greatly reduced.
Further, the calculating, according to the integral image, the adaptive threshold corresponding to each pixel point in the image to be processed includes: calculating the diagonal coordinates of the subareas corresponding to each pixel point in the image to be processed according to the size of the preset subareas; calculating the sum of pixel intensities of the corresponding sub-regions according to the diagonal coordinates; and calculating to obtain the self-adaptive threshold according to the sum of the pixel intensities and the number of the sub-region pixel points.
Further, the image of the corresponding sub-region is calculated according to the diagonal coordinatesSum of prime intensities comprising: according to the formulaCalculating the sum of pixel intensities of the corresponding sub-regions; wherein: />Is the sum of the pixel intensities of the sub-regions; intI i2,j2 The value corresponding to the pixel point of the j2 th row and the j2 nd column in the integral image; intI i2,j1-1 The value corresponding to the pixel point of the j1-1 column of the i2 row in the integral image; intI i1-1,j2 The value corresponding to the pixel point of the j2 th column of the i1-1 row in the integral image; intI i1-1,j1-1 The value corresponding to the pixel point of the j1-1 column of the i1-1 row in the integral image.
Further, the calculating to obtain the adaptive threshold according to the sum of the pixel intensities and the number of the sub-region pixels includes: according to the formulaCalculating to obtain the self-adaptive threshold value; wherein T is i,j The adaptive threshold value corresponding to the ith row and the jth column of pixel points is set; />Is the sum of the pixel intensities of the sub-regions; subH is the height of the subregion; subW is the width of the sub-region.
Further, obtaining an enhanced image of the image to be processed from the inverted image and the adaptive threshold, comprising: according to formula enI i,j ＝invI i,j -T i,j Calculating to obtain an intermediate enhanced image of the image to be processed; wherein: enI i,j The gray value corresponding to the ith row and the jth column of pixel points in the intermediate enhanced image is obtained; invI i,j The gray value corresponding to the pixel point of the ith row and the jth column in the reversed phase image; t (T) i,j The adaptive threshold value corresponding to the ith row and the jth column of pixel points is set; and carrying out normalization processing on the intermediate enhanced image to obtain the enhanced image.
According to the embodiment of the application, the intermediate enhanced image is normalized, so that the gray values of all pixel points in the obtained enhanced image are concentrated, and meanwhile, the gray value which is caused by subtracting the self-adaptive threshold value from the inverted image is prevented from being negative.
Further, the acquiring the inverted image corresponding to the image to be processed includes: and carrying out inversion processing on each pixel point in the image to be processed to obtain the inversion image.
The image to be processed is subjected to the reverse phase operation, so that the subsequent image to be processed is convenient to enhance.
In a second aspect, an embodiment of the present application provides an image processing apparatus including: the image acquisition module is used for acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object; the integral processing module is used for carrying out integral processing on the reversed phase image to obtain an integral image corresponding to the reversed phase image; the image processing module is used for obtaining the self-adaptive threshold value corresponding to each pixel point in the image to be processed according to the integral image calculation; and the image enhancement module is used for obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold.
In a third aspect, an embodiment of the present application provides an electronic device, including: the device comprises a processor, a memory and a bus, wherein the processor and the memory complete communication with each other through the bus; the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of the first aspect.
In a fourth aspect, embodiments of the present application provide a non-transitory computer readable storage medium comprising: the non-transitory computer-readable storage medium stores computer instructions that cause the computer to perform the method of the first aspect.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an image enhancement method according to an embodiment of the present application;
FIG. 2 (a) is a diagram of an image to be processed before rotation according to an embodiment of the present application;
FIG. 2 (b) is a rotated image to be processed according to an embodiment of the present application;
FIG. 2 (c) is an inverted image provided by an embodiment of the present application;
FIG. 2 (d) is an enhanced image provided by an embodiment of the present application;
FIG. 3 is a flowchart of a method for adaptive threshold calculation according to an embodiment of the present application;
FIG. 4 is a schematic view of a region of interest according to an embodiment of the present application;
FIG. 5 is a flowchart of another image enhancement method according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an image enhancement device according to an embodiment of the present application;
fig. 7 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.
Fig. 1 is a schematic flow chart of an image enhancement method provided by an embodiment of the present application, and as shown in fig. 1, the image enhancement method provided by the embodiment of the present application may be applied to a terminal device (may also be referred to as an electronic device) and a server; the terminal equipment can be a smart phone, a tablet personal computer, a personal digital assistant (Personal Digital Assitant, PDA) and the like; the server may be an application server or a Web server.
In order to facilitate understanding, the technical solution provided by the embodiments of the present application will be described below by taking a terminal device as an execution body as an example, where an application scenario for image enhancement provided by the embodiments of the present application is described.
Step 101: acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object;
step 102: integrating the reversed phase image to obtain an integrated image corresponding to the reversed phase image;
step 103: calculating according to the integral image to obtain an adaptive threshold corresponding to each pixel point in the image to be processed;
step 104: and obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold.
In step 101, the image to be processed may be a color image or a gray image, and if the image to be processed is a color image, the gray image may be converted to obtain a corresponding gray image. In addition, if the finger direction in the image to be processed is not the vertical direction, the image to be processed can be rotated, so that the finger direction in the rotated image to be processed is the vertical direction, and the execution of the subsequent steps is facilitated. FIG. 2 (a) is a diagram of an image to be processed before rotation according to an embodiment of the present application; FIG. 2 (b) is a rotated image to be processed according to an embodiment of the present application; the inverted image is obtained by inverting and normalizing the gray-scale image corresponding to the image to be processed, as shown in fig. 2 (c). The intermediate inverse image can be obtained specifically according to formula (1):
invI i,j ＝255-I i,j (1)
invI i,j the gray value corresponding to the pixel point of the ith row and the jth column in the middle reverse phase image; i i,j And the gray value corresponding to the pixel point in the j-th row and the j-th column in the image to be processed.
It should be noted that, before the image to be processed is acquired, an original image corresponding to the image to be processed may be acquired first, where the original image may include other objects besides the finger vein object, and in order to improve the subsequent calculation efficiency, the object recognition model may be used to perform object recognition on the original image, and a region of interest including the finger vein object is found out from the original image. And the region of interest is cut out from the original image and used as an image to be processed.
In step 102, an integral calculation is performed on each pixel in the inverted image to obtain an integrated value corresponding to each pixel, where the integrated values corresponding to all the pixels form an integral image, and a specific calculation method is described in the following embodiments.
In step 103, after the integral image is obtained, a corresponding adaptive threshold is obtained by calculation according to the value of each pixel point in the integral image in the image to be processed, and a specific calculation method is described in the following embodiments. It can be appreciated that the adaptive threshold is used to determine whether the corresponding pixel belongs to a finger vein, for example; the probability that the pixel point larger than the self-adaptive threshold is the finger vein is large, and conversely, the probability that the pixel point is small, the influence of noise such as illumination can be overcome by dynamically adjusting the threshold, and the probability of the finger vein is accurately estimated.
In step 104, the difference between the gray value of each pixel of the inverted image and the corresponding adaptive threshold is used as the gray value of the corresponding pixel in the enhanced image, so as to enhance the image to be processed, as shown in fig. 2 (d).
According to the embodiment of the application, the integral processing is carried out on the reverse image, the self-adaptive threshold value of each pixel point in the image to be processed is calculated, the enhanced image of the image to be processed is obtained according to the self-adaptive threshold value and the reverse image, and the finger vein in the image is well distinguished from the background through the foreground enhancement of the image to be processed, so that the definition of the finger vein in the image to be processed is improved.
On the basis of the foregoing embodiment, the integrating the inverted image to obtain an integrated image corresponding to the inverted image includes:
calculating the gray value of each pixel point in the inverse image in an integral image according to a formula (2) to obtain the integral image; wherein:
IntI i,j ＝invI i,j +IntI i-1,j +IntI i,j-1 -IntI i-1,j-1 (2)
IntI i,j the value of the pixel point in the ith row and the jth column in the integral image; invI i,j The gray value corresponding to the ith row and the jth column of pixel points in the inverted image is obtained; intI i-1,j The value of the pixel point corresponding to the j-th row of the i-1 row in the integral image is obtained; intI i,j-1 The value of the pixel point of the j-1 th row in the integral image; intI i-1,j-1 The value of the pixel point of the j-1 th row and the j-1 th column in the integral image.
Based on the above embodiment, as shown in fig. 3, step 103 specifically includes:
step 1031: and calculating the diagonal coordinates of the subareas corresponding to each pixel point in the image to be processed according to the size of the preset subareas.
The determination method of the size of the subarea is as follows:
the parameter alpha e 0,1 is set as an adaptive proportion of the width of the sub-area. And vertically dividing the finger vein image into subareas according to the width subW, wherein a calculation formula of subW is shown in a formula (3). For example: for a finger vein ROIs image with a width of 60, α=0.2 is set, thereby obtaining a rectangular region with a width of 3. Similarly, the parameter beta epsilon [0,1] is set as the self-adaptive proportion of the height of the subarea, the self-adaptive height of the subarea is calculated according to the formula (3), and the heights and widths of the subareas are respectively subH and subW. For example: for a finger vein ROIs image of height 128, β=0.11 is set, so that sub-areas of height-width [15,3] are obtained, respectively, and the sub-areas can cover the finger vein object. It should be noted that the values of α and β may be set according to historical experience, or may be found by multiple tests, which is not particularly limited in the embodiment of the present application.
Taking each pixel point in the image to be processed as a center point, determining a diagonal coordinate according to the size of the sub-region, and assuming that the size of the sub-region is 3*3 and the pixel points in the 3 rd row and the 3 rd column are taken as the pixel points, as shown in fig. 4, it can be understood that in the embodiment of the application, the pixel point currently taken as the center point in the image to be processed is called the processed pixel point. Then the set of diagonal coordinates for the pixel under processing is (2, 2) and (4, 4), and embodiments of the present application are described with the upper left corner and the lower right corner as the set of diagonal coordinates. Of course, another set of diagonal coordinates, namely (2, 4) and (4, 2), may also be selected. It should be noted that if the upper right and lower left angular coordinates are adopted as the diagonal coordinates, the above formula (2) also requires a corresponding transformation.
Step 1032: and calculating the sum of the pixel intensities of the corresponding sub-regions according to the diagonal coordinates.
Calculating the sum of the pixel intensities of the corresponding sub-regions according to formula (4); wherein:
is the sum of the pixel intensities of the sub-regions; intI i2,j2 The value corresponding to the pixel point of the j2 th row and the j2 nd column in the integral image; intI i2,j1-1 The value corresponding to the pixel point of the j1-1 column of the i2 row in the integral image; intI i1-1,j2 The value corresponding to the pixel point of the j2 th column of the i1-1 row in the integral image; intI i1-1,j1-1 The value corresponding to the pixel point of the j1-1 column of the i1-1 row in the integral image.
Step 1033: and calculating to obtain the self-adaptive threshold according to the sum of the pixel intensities and the number of the sub-region pixel points.
Calculating according to formula (5) to obtain the adaptive threshold; wherein:
T i,j the adaptive threshold value corresponding to the ith row and the jth column of pixel points is set;is the sum of the pixel intensities of the sub-regions; subH is the height of the subregion; subW is the width of the sub-region.
The embodiment of the application obtains clearer finger vein images by a mode based on foreground enhancement.
On the basis of the above embodiment, obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold includes:
calculating to obtain an intermediate enhanced image of the image to be processed according to a formula (6); wherein:
enI i,j ＝invI i,j -T i,j (6)
enI i,j the gray value corresponding to the ith row and the jth column of pixel points in the intermediate enhanced image is obtained; invI i,j The gray value corresponding to the pixel point of the ith row and the jth column in the reversed phase image; t (T) i,j The adaptive threshold value corresponding to the ith row and the jth column of pixel points is set;
and carrying out normalization processing on the intermediate enhanced image to obtain the enhanced image.
Wherein, during normalization processing, the maximum gray value enI of the pixel points in the intermediate enhanced image is obtained max And a minimum gray value enI min And (3) calculating according to a formula (7) to obtain the normalized gray value of each pixel. Wherein:
enI′ i,j normalized gray values corresponding to the ith row and the jth column of pixel points in the intermediate enhanced image; enI i,j The gray value corresponding to the ith row and the jth column of pixel points in the intermediate enhanced image is obtained; enI max Enhancing images for intermediariesMaximum gray value of the middle pixel point; enI min Is the minimum gray value of the pixel point in the intermediate enhanced image.
It can be understood that, in addition to enabling the gray values of the pixels of the intermediate enhanced image to be relatively close to each other, when the gray values corresponding to the pixels in the intermediate enhanced image are calculated, negative numbers may occur when the gray values of the pixels in the inverted image are subtracted from the adaptive threshold, and another purpose of normalization is to limit the gray values between [0,1 ].
Fig. 5 is a schematic flow chart of another image enhancement method according to an embodiment of the present application, as shown in fig. 5, including:
step 501: inverting the gray value of the image; the terminal equipment acquires an image to be processed containing the finger vein object, and performs inversion processing on the image to be processed to acquire an inverted image.
Step 502: calculating an integral image of the inverted image; an integral image of the inverted image is calculated according to formula (2).
Step 503: calculating the size of a sub-region where the pixel point to be processed is located; the size of the sub-region where the processed pixel point is located can be obtained by calculation according to the formula (3). It should be noted that a pixel in an image to be processed is referred to as a processed pixel.
Step 504: averaging the subareas corresponding to the pixel points to be processed, and determining the self-adaptive threshold value of the pixel points; it should be noted that, the mean value of the gray values of the sub-regions corresponding to the processed pixel points is obtained, and the specific calculation method is shown in the formula (5).
Step 505: and carrying out difference and normalization on the inverted image and the self-adaptive threshold value to obtain an enhanced image.
According to the embodiment of the application, the integral processing is carried out on the reverse phase image, the self-adaptive threshold value of each pixel point in the image to be processed is calculated, the enhanced image of the image to be processed is obtained according to the self-adaptive threshold value and the reverse phase image, and the definition of the finger veins in the image to be processed is improved through the enhancement of the image to be processed.
Fig. 6 is a schematic structural diagram of an image enhancement apparatus according to an embodiment of the present application, where the apparatus may be a module, a program segment, or a code on an electronic device. It should be understood that the apparatus corresponds to the embodiment of the method of fig. 1 described above, and is capable of performing the steps involved in the embodiment of the method of fig. 1, and specific functions of the apparatus may be referred to in the foregoing description, and detailed descriptions thereof are omitted herein as appropriate to avoid redundancy. The device comprises: an image acquisition module 601, an integration processing module 602, an image processing module 603, and an image enhancement module 604, wherein:
the image acquisition module 601 is configured to acquire an image to be processed and an inverted image corresponding to the image to be processed, where the image to be processed includes a finger vein object; the integration processing module 602 is configured to perform integration processing on the inverted image to obtain an integrated image corresponding to the inverted image; the image processing module 603 is configured to obtain an adaptive threshold corresponding to each pixel point in the image to be processed according to the integral image calculation; the image enhancement module 604 is configured to obtain an enhanced image of the image to be processed according to the inverted image and the adaptive threshold.
Based on the above embodiment, the integration processing module 602 is specifically configured to:
according to the formula IntI i,j ＝invI i,j +IntI i-1,j +IntI i,j-1 -IntI i-1,j-1 Calculating the gray value of each pixel point in the inverse image in an integral image to obtain the integral image; wherein:
IntI i,j the value of the pixel point in the ith row and the jth column in the integral image; invI i,j The gray value corresponding to the ith row and the jth column of pixel points in the inverted image is obtained; intI i-1,j The value of the pixel point corresponding to the j-th row of the i-1 row in the integral image is obtained; intI i,j-1 The value of the pixel point of the j-1 th row in the integral image; intI i-1,j-1 The value of the pixel point of the j-1 th row and the j-1 th column in the integral image.
On the basis of the above embodiment, the image processing module 603 is specifically configured to:
calculating the diagonal coordinates of the subareas corresponding to each pixel point in the image to be processed according to the size of the preset subareas;
calculating the sum of pixel intensities of the corresponding sub-regions according to the diagonal coordinates;
and calculating to obtain the self-adaptive threshold according to the sum of the pixel intensities and the number of the sub-region pixel points.
On the basis of the above embodiment, the image processing module 603 is specifically configured to:
according to the formulaCalculating the sum of pixel intensities of the corresponding sub-regions; wherein:
is the sum of the pixel intensities of the sub-regions; intI i2,j2 The value corresponding to the pixel point of the j2 th row and the j2 nd column in the integral image; intI i2,j1-1 The value corresponding to the pixel point of the j1-1 column of the i2 row in the integral image; intI i1-1,j2 The value corresponding to the pixel point of the j2 th column of the i1-1 row in the integral image; intI i1-1,j1-1 The value corresponding to the pixel point of the j1-1 column of the i1-1 row in the integral image.
On the basis of the above embodiment, the image processing module 603 is specifically configured to:
according to the formulaCalculating to obtain the self-adaptive threshold value; wherein,
T i,j the adaptive threshold value corresponding to the ith row and the jth column of pixel points is set;is the sum of the pixel intensities of the sub-regions; subH is the height of the subregion; subW is the width of the sub-region.
Based on the above embodiment, the image enhancement module 604 is specifically configured to:
according to formula enI i,j ＝invI i,j -T i,j Calculating to obtain an intermediate enhanced image of the image to be processed; wherein:
enI i,j the gray value corresponding to the ith row and the jth column of pixel points in the intermediate enhanced image is obtained; invI i,j The gray value corresponding to the pixel point of the ith row and the jth column in the reversed phase image; t (T) i,j The adaptive threshold value corresponding to the ith row and the jth column of pixel points is set;
and carrying out normalization processing on the intermediate enhanced image to obtain the enhanced image.
On the basis of the above embodiment, the image acquisition module 601 is specifically configured to:
and carrying out inversion processing on each pixel point in the image to be processed to obtain the inversion image.
Fig. 7 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present application, as shown in fig. 7, where the electronic device includes: a processor (processor) 701, a memory (memory) 702, and a bus 703; wherein,
the processor 701 and the memory 702 perform communication with each other through the bus 703;
the processor 701 is configured to invoke the program instructions in the memory 702 to perform the methods provided in the above method embodiments, for example, including: acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object; integrating the reversed phase image to obtain an integrated image corresponding to the reversed phase image; calculating and obtaining an adaptive threshold corresponding to each pixel point in the region of interest according to the integral image; and obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold.
The processor 701 may be an integrated circuit chip having signal processing capabilities. The processor 701 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), and the like; but may also be a Digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. Which may implement or perform the various methods, steps, and logical blocks disclosed in embodiments of the application. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The Memory 702 may include, but is not limited to, random access Memory (Random Access Memory, RAM), read Only Memory (ROM), programmable Read Only Memory (Programmable Read-Only Memory, PROM), erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable Read Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), and the like.
The present embodiment discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, are capable of performing the methods provided by the above-described method embodiments, for example comprising: acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object; integrating the reversed phase image to obtain an integrated image corresponding to the reversed phase image; calculating and obtaining an adaptive threshold corresponding to each pixel point in the region of interest according to the integral image; and obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold.
The present embodiment provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described method embodiments, for example, including: acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object; integrating the reversed phase image to obtain an integrated image corresponding to the reversed phase image; calculating and obtaining an adaptive threshold corresponding to each pixel point in the region of interest according to the integral image; and obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
Further, the units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Furthermore, functional modules in various embodiments of the present application may be integrated together to form a single portion, or each module may exist alone, or two or more modules may be integrated to form a single portion.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and variations will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (9)
1. An image enhancement method, comprising:
acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object;
integrating the reversed phase image to obtain an integrated image corresponding to the reversed phase image;
calculating according to the integral image to obtain an adaptive threshold corresponding to each pixel point in the image to be processed;
obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold;
obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold, including:
according to the formulaCalculating to obtain an intermediate enhanced image of the image to be processed; wherein:
the gray value corresponding to the ith row and the jth column of pixel points in the intermediate enhanced image is obtained; />The gray value corresponding to the pixel point of the ith row and the jth column in the reversed phase image; />The adaptive threshold value corresponding to the ith row and the jth column of pixel points is set;
and carrying out normalization processing on the intermediate enhanced image to obtain the enhanced image.
2. The method according to claim 1, wherein the integrating the inverted image to obtain an integrated image corresponding to the inverted image includes:
according to the formulaCalculating each pixel point in the reversed phase imageIntegrating values in an image to obtain the integrated image; wherein:
the value of the pixel point in the ith row and the jth column in the integral image; />The gray value corresponding to the ith row and the jth column of pixel points in the inverted image is obtained; />The value of the pixel point corresponding to the j-th row of the i-1 row in the integral image is obtained; />The value of the pixel point of the j-1 th row in the integral image; />The value of the pixel point of the j-1 th row and the j-1 th column in the integral image.
3. The method according to claim 1, wherein the calculating, according to the integral image, an adaptive threshold value corresponding to each pixel point in the image to be processed includes:
calculating the diagonal coordinates of the subareas corresponding to each pixel point in the image to be processed according to the size of the preset subareas;
calculating the sum of pixel intensities of the corresponding sub-regions according to the diagonal coordinates;
and calculating according to the sum of the pixel intensities and the number of the sub-region pixel points to obtain the self-adaptive threshold.
4. A method according to claim 3, wherein said calculating the sum of pixel intensities of the corresponding sub-regions from the diagonal coordinates comprises:
according to the formulaCalculating the sum of pixel intensities of the corresponding sub-regions; wherein:
is the sum of the pixel intensities of the sub-regions; />For the +.>Line->A value corresponding to a pixel point of the column; />For the +.>Line->A value corresponding to a pixel point of the column; />For the +.>Line->A value corresponding to a pixel point of the column; />For the +.>Line->The value corresponding to the pixel point of the column.
5. The method of claim 4, wherein calculating the adaptive threshold based on the sum of the pixel intensities and the number of sub-region pixels comprises:
according to the formulaCalculating to obtain the self-adaptive threshold value; wherein,
is->Line->An adaptive threshold corresponding to the column pixel points; />Is the sum of the pixel intensities of the sub-regions; />Is the height of the subregion; />Is the width of the sub-region.
6. The method according to claim 1, wherein the acquiring an inverted image corresponding to the image to be processed includes:
and carrying out inversion processing on each pixel point in the image to be processed to obtain the inversion image.
7. An image enhancement apparatus, comprising:
the image acquisition module is used for acquiring an image to be processed and an inverted image corresponding to the image to be processed, wherein the image to be processed comprises a finger vein object;
the integral processing module is used for carrying out integral processing on the reversed phase image to obtain an integral image corresponding to the reversed phase image;
the image processing module is used for obtaining the self-adaptive threshold value corresponding to each pixel point in the image to be processed according to the integral image calculation;
the image enhancement module is used for obtaining an enhanced image of the image to be processed according to the inverted image and the adaptive threshold;
the image enhancement module is specifically configured to:
according to the formulaCalculating to obtain an intermediate enhanced image of the image to be processed; wherein:
the gray value corresponding to the ith row and the jth column of pixel points in the intermediate enhanced image is obtained; />The gray value corresponding to the pixel point of the ith row and the jth column in the reversed phase image; />The adaptive threshold value corresponding to the ith row and the jth column of pixel points is set;
and carrying out normalization processing on the intermediate enhanced image to obtain the enhanced image.
8. An electronic device, comprising: a processor, a memory, and a bus, wherein,
the processor and the memory complete communication with each other through the bus;
the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1-6.
9. A non-transitory computer readable storage medium storing computer instructions which, when executed by a computer, cause the computer to perform the method of any of claims 1-6.
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