CN109858363B - Dog nose print feature point detection method, device, system and storage medium - Google Patents
Dog nose print feature point detection method, device, system and storage medium Download PDFInfo
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- CN109858363B CN109858363B CN201811625868.5A CN201811625868A CN109858363B CN 109858363 B CN109858363 B CN 109858363B CN 201811625868 A CN201811625868 A CN 201811625868A CN 109858363 B CN109858363 B CN 109858363B
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Abstract
The invention provides a method, a device and a system for detecting dog nose print characteristic points and a storage medium. The method for detecting the dog nose print characteristic points comprises the following steps: obtaining the coordinate deviation of the dog nose print characteristic points in the dog nose image and the corresponding dog nose print reference characteristic points based on the dog nose image and the trained dog nose print model; and obtaining the coordinates of the dog nose print characteristic points in the dog nose image according to the coordinates of the dog nose print reference characteristic points and the coordinate deviation. According to the method, the device, the system and the storage medium, the accuracy and the real-time performance of the dog nose print characteristic point detection and the running speed can be effectively improved.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to processing of a dog face image.
Background
The feature point marking is used as an important step before image alignment, and the overall performance of an image recognition, analysis and search system is greatly influenced. At present, in the process of face recognition, a plurality of effective feature point labeling methods exist, but the methods for labeling feature points in animal recognition are very few, in addition, the calculation time, the complexity and the number of the feature points are in direct proportion, the more feature points to be detected, the more detectors are needed, and the implementation is difficult in the application of the dense feature points.
Therefore, a better method for detecting the dog face characteristic points is lacked in the prior art, the traditional characteristic point detection method is greatly influenced by fine disturbance and easily causes report omission or false report, so that the accuracy and recall rate are low, and the operation efficiency is not high.
Disclosure of Invention
The present invention has been made in view of the above problems. The invention provides a dog nose print feature point detection method, a dog nose print feature point detection device, a dog nose print feature point detection system and a computer storage medium.
According to an aspect of the present invention, a method for detecting dog nose print feature points is provided, including:
obtaining the coordinate deviation of the dog nose print characteristic points in the dog nose image and the corresponding dog nose print reference characteristic points based on the dog nose image and the trained dog nose print model;
and obtaining the coordinates of the dog nose print characteristic points in the dog nose image according to the coordinates of the dog nose print reference characteristic points and the deviation.
Illustratively, the training of the dog nose print model comprises:
marking characteristic points of the dog nose print in the dog nose print training sample image based on a preset rule, and obtaining coordinates of the corresponding reference characteristic points of the dog nose print;
calculating the coordinate deviation between the characteristic point of the dog nose print in the marked dog nose print training sample image and the corresponding reference characteristic point of the dog nose print;
and training the dog nose print model according to the marked dog nose print training sample image and the corresponding coordinate deviation to obtain the trained dog nose print model.
Illustratively, the obtaining the coordinates of the reference feature point of the corresponding dog nose print includes: and averaging the coordinates of the same characteristic point of the dog nose print in the marked dog nose print training sample image to obtain the corresponding coordinates of the dog nose print reference characteristic point.
Illustratively, the predetermined rule includes labeling based on at least one of a nostril contour, a nose contour of the dog's nose.
Illustratively, the feature point labeling based on the nose contour of the dog nose comprises: marking characteristic points of the junction of the vertical line of the center of the dog nose and the boundaries of the upper side and the lower side of the nose outline, and marking characteristic points of the junction of the horizontal line of the center of the dog nose and the boundaries of the left side and the right side of the nose outline.
Illustratively, the labeling of feature points based on the nose contour of the dog nose further comprises: and marking characteristic points along the nose contour at equal intervals by taking the characteristic points of intersection of the vertical line of the center of the nose of the dog and the horizontal line of the center of the nose of the dog and the boundary of the nose contour as a reference.
Illustratively, characterizing the feature points based on the nostril contours of the dog's nose comprises: marking characteristic points of the junction of a left nostril center vertical line and the upper and lower side boundaries of the left nostril outline, and characteristic points of the junction of a left nostril center horizontal line and the left and right side boundaries of the left nostril outline; and
and
marking characteristic points of the junction of the right nostril center vertical line and the upper and lower side boundaries of the right nostril outline, and characteristic points of the junction of the right nostril center horizontal line and the left and right side boundaries of the right nostril outline.
Illustratively, the labeling feature points based on the nostril contour of the dog nose further comprises: marking characteristic points along the contour of the left nostril at equal intervals by taking the characteristic points of the intersection of the central vertical line of the left nostril and the central horizontal line of the left nostril and the contour of the left nostril as a reference; and
and taking the feature points of the intersection of the right nostril center vertical line and the right nostril center horizontal line with the right nostril outline as a reference, and marking the feature points at equal intervals along the right nostril outline.
According to another aspect of the present invention, there is provided a device for detecting dog nose print feature points, comprising:
the detection module is used for obtaining the coordinate deviation of the dog nose print characteristic points in the dog nose image and the corresponding dog nose print reference characteristic points based on the dog nose image and the trained dog nose print model;
and the coordinate calculation module is used for obtaining the coordinates of the dog nose print characteristic points in the dog nose image according to the coordinates of the dog nose print reference characteristic points and the coordinate deviation.
Illustratively, the training of the dog nose print model comprises:
marking characteristic points of the dog nose print in the dog nose print training sample image based on a preset rule, and obtaining coordinates of the corresponding reference characteristic points of the dog nose print;
calculating the coordinate deviation between each characteristic point of the dog nose print in the marked dog nose print training sample image and the corresponding reference characteristic point of the dog nose print;
and training the dog nose print model according to the marked dog nose print training sample image and the corresponding coordinate deviation to obtain the trained dog nose print model.
Illustratively, the obtaining the coordinates of the reference feature point of the corresponding dog nose print includes: and averaging the coordinates of the same characteristic point of the dog nose print in the marked dog nose print training sample image to obtain the coordinates of the dog nose print reference characteristic point.
Illustratively, the predetermined rule includes labeling based on at least one of a nostril contour, a nose contour of the dog's nose.
Illustratively, the feature point labeling based on the nose contour of the dog nose comprises: marking the characteristic points of the junction of the vertical line of the dog nose center and the upper and lower side boundaries of the nose outline, and the characteristic points of the junction of the horizontal line of the dog nose center and the left and right side boundaries of the nose outline.
Illustratively, the labeling of feature points based on the nose contour of the dog nose further comprises: and taking the feature points of intersection of the vertical line of the center of the dog nose, the horizontal line of the center of the dog nose and the boundary of the nose contour as a reference, and marking the feature points at equal intervals along the nose contour.
Illustratively, characterizing the feature points based on the nostril contours of the dog's nose comprises: marking characteristic points of the junction of a left nostril center vertical line and the upper and lower side boundaries of the left nostril outline, and characteristic points of the junction of a left nostril center horizontal line and the left and right side boundaries of the left nostril outline; and marking characteristic points of the junction of the right nostril center vertical line and the upper and lower side boundaries of the right nostril outline, and characteristic points of the junction of the right nostril center horizontal line and the left and right side boundaries of the right nostril outline.
Illustratively, the labeling feature points based on the nostril contour of the dog nose further comprises: marking characteristic points at equal intervals along the contour of the left nostril by taking the characteristic points of the intersection of the central vertical line of the left nostril and the central horizontal line of the left nostril and the contour of the left nostril as a reference; and
and taking the feature points of the intersection of the right nostril center vertical line and the right nostril center horizontal line with the right nostril outline as a reference, and marking the feature points at equal intervals along the right nostril outline.
Illustratively, the coordinate calculation module is further configured to: and adding the coordinate of the dog nose print reference characteristic point to the coordinate deviation to obtain the coordinate of the dog nose print characteristic point in the dog nose image.
According to another aspect of the present invention, there is provided a dog nose print feature point detection system, comprising a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above method when executing the computer program.
According to another aspect of the present invention, there is provided a computer readable storage medium having a computer program stored thereon, wherein the computer program is adapted to carry out the steps of the above-mentioned method when executed by a computer.
According to the method, the device and the system for detecting the dog nose print characteristic points and the computer storage medium, provided by the embodiment of the invention, the coordinates of the dog nose print characteristic points are obtained by combining a simple labeling method and model regression, so that the accuracy and the real-time property of the detection of the dog nose print characteristic points can be effectively improved, and the operation efficiency is high.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail embodiments of the present invention with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings, like reference numbers generally represent like parts or steps.
FIG. 1 is a schematic block diagram of an example electronic device for implementing a dog nose print feature point detection method and apparatus in accordance with embodiments of the invention;
FIG. 2 is a schematic flow chart of a method for detecting dog nose print feature points according to an embodiment of the invention;
FIG. 3 is an example of a dog nose image annotated with dog nose print feature points, according to an embodiment of the invention;
FIG. 4 is a schematic block diagram of a dog nose print feature point detection apparatus according to an embodiment of the present invention;
fig. 5 is a schematic block diagram of a dog nose print feature point detection system according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely a subset of embodiments of the invention and not all embodiments of the invention, with the understanding that the invention is not limited to the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the invention described herein without inventive step, shall fall within the scope of protection of the invention.
First, an example electronic device 100 for implementing the dog nose print feature point detection method and apparatus according to an embodiment of the present invention is described with reference to fig. 1.
As shown in FIG. 1, electronic device 100 includes one or more processors 101, one or more memory devices 102, an input device 103, an output device 104, an image sensor 105, which are interconnected via a bus system 106 and/or other form of connection mechanism (not shown). It should be noted that the components and structure of the electronic device 100 shown in fig. 1 are exemplary only, and not limiting, and the electronic device may have other components and structures as desired.
The processor 101 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 100 to perform desired functions.
The storage 102 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. On which one or more computer program instructions may be stored that may be executed by processor 102 to implement client-side functionality (implemented by the processor) and/or other desired functionality in embodiments of the invention described below. Various applications and various data, such as various data used and/or generated by the applications, may also be stored in the computer-readable storage medium.
The input device 103 may be a device used by a user to input instructions, and may include one or more of a keyboard, a mouse, a microphone, a touch screen, and the like.
The output device 104 may output various information (e.g., images or sounds) to an external (e.g., user), and may include one or more of a display, a speaker, and the like.
The image sensor 105 may take an image (e.g., a photograph, a video, etc.) desired by the user and store the taken image in the storage device 102 for use by other components.
For example, an example electronic device for implementing the method and apparatus for detecting dog nose print feature points according to the embodiment of the present invention may be implemented as a smart phone, a tablet computer, a video capture terminal of an access control system, or the like.
Next, a method 200 for detecting dog nose print feature points according to an embodiment of the present invention will be described with reference to fig. 2.
Firstly, in step S210, obtaining a coordinate deviation between a dog nose print feature point in a dog nose image and each corresponding dog nose print reference feature point based on the dog nose image and a trained dog nose print model;
in step S220, the coordinates of each dog nose print feature point in the dog nose image are obtained according to each dog nose print reference feature point and the coordinate deviation.
The dog nose print is similar to human fingerprints, the shape of the print is not influenced due to the time lapse, and the dog nose print can become a unique identification mark of each dog, so that the marking of the dog nose print can be used as a data base for subsequent identification. Each dog nose print reference feature point is obtained from mixed data of a large number of identities, so that the reference of the feature point can be represented, but the reference does not have the capability of representing specific identities, so that the coordinates of the dog nose print feature point in each dog nose print image can be accurately obtained only by establishing a regression model to calculate the coordinate deviation between the dog nose print feature point and each dog nose print reference feature point in each dog nose print image. Compared with a detection model which is trained and established after a large number of different dog nose print images are directly adopted to mark dog nose print characteristic points, the method greatly reduces the calculated amount and improves the detection efficiency; the problems that the traditional characteristic point marking and detecting method is very sensitive to illumination change, posture change and the like and is poor in robustness can be solved.
Illustratively, the method for detecting dog nose print characteristic points according to the embodiment of the invention can be implemented in a device, an apparatus or a system having a memory and a processor.
The method for detecting the dog nose print characteristic points can be deployed at an image acquisition end, for example, the method can be deployed at the image acquisition end of an access control system; may be deployed at a personal terminal such as a smart phone, tablet, personal computer, etc. Alternatively, the detection method for dog nose print feature points according to the embodiment of the present invention may also be distributively deployed at a server side (or cloud side) and a personal terminal side.
According to the detection method of the dog nose print characteristic points, the coordinates of the dog nose print characteristic points are obtained by combining a simple labeling method and model regression, the accuracy and the real-time performance of the detection of the dog nose print characteristic points can be effectively improved, and the operation efficiency is high.
According to an embodiment of the present invention, step 210 may further include: the training of the dog nose print model comprises the following steps:
marking characteristic points of the dog nose print in the dog nose print training sample image based on a preset rule, and obtaining coordinates of the corresponding reference characteristic points of the dog nose print;
calculating the coordinate deviation between each characteristic point of the dog nose print in the marked dog nose print training sample image and the corresponding reference characteristic point of the dog nose print;
and training the dog nose print model according to the marked dog nose print training sample image and the corresponding coordinate deviation to obtain the trained dog nose print model.
Illustratively, the obtaining the coordinates of the reference feature point of the corresponding dog nose print includes: and averaging the coordinates of the same characteristic point of the dog nose print in the marked dog nose print training sample image to obtain the coordinates of the dog nose print reference characteristic point.
As mentioned above, the dog nose print reference feature point is obtained from a mixture of a plurality of identities, and is used as a reference for representing the dog nose print feature point. For example, N dog nose images are selected to label the characteristic points of the dog nose print in the same manner, wherein N dog nose print characteristic points are labeled on each dog nose image, and N and N are natural numbers; then the coordinate of the ith dog nose print reference feature point is the average coordinate of all the ith dog nose print coordinates in the 1 st to nth dog nose images, i is 1,2, … …, N.
Illustratively, the predetermined rule includes labeling based on at least one of a nostril contour, a nose contour of the dog's nose.
Illustratively, the feature point labeling based on the nose contour of the dog nose comprises: marking the characteristic points of the junction of the vertical line of the dog nose center and the upper and lower side boundaries of the nose outline, and the characteristic points of the junction of the horizontal line of the dog nose center and the left and right side boundaries of the nose outline.
Illustratively, the labeling of feature points based on the nose contour of the dog nose further comprises: and taking the feature points of intersection of the vertical line of the center of the dog nose, the horizontal line of the center of the dog nose and the boundary of the nose contour as a reference, and marking the feature points at equal intervals along the nose contour.
Illustratively, characterizing the feature points based on the nostril contours of the dog's nose comprises: marking characteristic points of the junction of a left nostril center vertical line and the upper and lower side boundaries of the left nostril outline, and characteristic points of the junction of a left nostril center horizontal line and the left and right side boundaries of the left nostril outline; and marking characteristic points of the junction of the right nostril center vertical line and the upper and lower side boundaries of the right nostril outline, and characteristic points of the junction of the right nostril center horizontal line and the left and right side boundaries of the right nostril outline.
Illustratively, the labeling feature points based on the nostril contour of the dog nose further comprises: marking characteristic points at equal intervals along the contour of the left nostril by taking the characteristic points of the intersection of the central vertical line of the left nostril and the central horizontal line of the left nostril and the contour of the left nostril as a reference; and
and taking the feature points of the intersection of the right nostril center vertical line and the right nostril center horizontal line with the right nostril outline as a reference, and marking the feature points at equal intervals along the right nostril outline.
In one embodiment, as shown in fig. 3, a dog nose image is taken as an example to illustrate labeling of a dog face according to a predetermined specification. Specifically, feature point labeling is performed based on two basic positions, namely a nostril outline and a nose outline of the dog nose in the dog nose image shown in fig. 3.
Firstly, marking characteristic points based on the nose contour of the nose of the dog, and specifically comprising the following steps: marking characteristic points 1 and 2 of the junction of the vertical line of the dog nose center and the boundaries of the upper side and the lower side of the nose outline, and marking characteristic points 3 and 4 of the junction of the horizontal line of the dog nose center and the boundaries of the left side and the right side of the nose outline; use the crossing four characteristic points of 1,2, 3, 4 of dog nose center vertical line and dog nose center horizontal line and nose profile border as the benchmark, divide into four bold with the nose profile, along the nose profile, two characteristic points are annotated to every equidistance mark, 8 characteristic points are annotated to total equidistance: 5. 6, 7, 8, 9, 10, 11, 12;
then, feature point labeling is carried out based on the nostril outline of the dog nose, and the method specifically comprises the following steps: marking characteristic points 13 and 14 which are connected with the upper and lower side boundaries of the outline of the left nostril and a central vertical line of the left nostril, and characteristic points 15 and 16 which are connected with the left and right side boundaries of the left nostril and a central horizontal line of the left nostril; use four characteristic points 13, 14, 15, 16 of the characteristic point of left nostril central vertical line and left nostril central horizontal line and left nostril profile handing-over as the benchmark, divide into four bold with left nostril profile, along left nostril profile, every piece equidistance marks a characteristic point, 4 characteristic points of total equidistance mark: 17. 18, 19, 20; and
marking characteristic points 21 and 22 for the junction of a right nostril center vertical line and the upper and lower side boundaries of the right nostril outline, and characteristic points 24 and 23 for the junction of a right nostril center horizontal line and the left and right side boundaries of the right nostril; use four characteristic points 21, 22, 23, 24 of the characteristic point of right nostril center vertical line and right nostril center horizontal line and right nostril profile handing-over as the benchmark, divide into four bold with right nostril profile, along right nostril profile, every piece equidistance marks a characteristic point, 4 characteristic points of total equidistance mark: 25. 26, 27, 28.
Therefore, feature point labeling is carried out on the dog nose print in the dog nose print training sample image based on a preset rule, finally 8 feature points are labeled circularly for each nostril on each side, 12 feature points are labeled circularly for the nose contour, and the total number of the feature points is 28.
It should be noted that the labeling step in this embodiment is only an example, and does not represent the labeling step of the predetermined rule; the predetermined rule has no limitation on the labeling order. In addition, the predetermined rule can increase the number of the feature points according to the design requirement and the actual situation so as to improve the accuracy of the annotation and provide a good data base for the subsequent procedure.
According to an embodiment of the present invention, step 220 may further include: and adding the coordinate of the dog nose print reference characteristic point to the coordinate deviation to obtain the coordinate of the dog nose print characteristic point in the dog nose image.
Fig. 4 shows a schematic block diagram of a detection apparatus 400 for dog nose print feature points according to an embodiment of the present invention. As shown in fig. 4, the apparatus 400 for detecting dog nose print feature points according to the embodiment of the present invention includes:
the detection module 410 is configured to obtain feature points of dog nose streaks in the dog nose image and coordinate deviations between the feature points of the dog nose streaks and corresponding reference feature points of the dog nose streaks based on the dog nose image and the trained dog nose streak model;
and the coordinate calculation module 420 is configured to obtain coordinates of each dog nose print feature point in the dog nose image according to the coordinates of the dog nose print reference feature points and the coordinate deviation.
Illustratively, the training of the dog nose print model comprises:
marking characteristic points of the dog nose print in the dog nose print training sample image based on a preset rule, and obtaining coordinates of the corresponding reference characteristic points of the dog nose print;
calculating the coordinate deviation between each characteristic point of the dog nose print in the marked dog nose print training sample image and the corresponding reference characteristic point of the dog nose print;
and training the dog nose print model according to the marked dog nose print training sample image and the corresponding coordinate deviation to obtain the trained dog nose print model.
Illustratively, the obtaining the coordinates of the reference feature point of the corresponding dog nose print includes: and averaging the coordinates of the same characteristic point of the dog nose print in the marked dog nose print training sample image to obtain the coordinates of the dog nose print reference characteristic point.
Illustratively, the predetermined rule includes labeling based on at least one of a nostril contour, a nose contour of the dog's nose.
Illustratively, the feature point labeling based on the nose contour of the dog nose comprises: marking the characteristic points of the junction of the vertical line of the dog nose center and the upper and lower side boundaries of the nose outline, and the characteristic points of the junction of the horizontal line of the dog nose center and the left and right side boundaries of the nose outline.
Illustratively, the labeling of feature points based on the nose contour of the dog nose further comprises: and taking the feature points of intersection of the vertical line of the center of the dog nose, the horizontal line of the center of the dog nose and the boundary of the nose contour as a reference, and marking the feature points at equal intervals along the nose contour.
Illustratively, characterizing the feature points based on the nostril contours of the dog's nose comprises: marking characteristic points of the junction of a left nostril center vertical line and the upper and lower side boundaries of the left nostril outline, and characteristic points of the junction of a left nostril center horizontal line and the left and right side boundaries of the left nostril outline; and marking characteristic points of the junction of the right nostril center vertical line and the upper and lower side boundaries of the right nostril outline, and characteristic points of the junction of the right nostril center horizontal line and the left and right side boundaries of the right nostril outline.
Illustratively, the labeling feature points based on the nostril contour of the dog nose further comprises: marking characteristic points at equal intervals along the contour of the left nostril by taking the characteristic points of the intersection of the central vertical line of the left nostril and the central horizontal line of the left nostril and the contour of the left nostril as a reference; and
and taking the feature points of the intersection of the right nostril center vertical line and the right nostril center horizontal line with the right nostril outline as a reference, and marking the feature points at equal intervals along the right nostril outline.
According to an embodiment of the present invention, the coordinate calculation module 420 is further configured to: and adding the coordinate of the dog nose print reference characteristic point to the coordinate deviation to obtain the coordinate of the dog nose print characteristic point in the dog nose image.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
Fig. 5 shows a schematic block diagram of a dog nose print feature point detection system 500 according to an embodiment of the invention. The detection system 500 for dog nose print feature points includes an image sensor 510, a storage device 520, and a processor 530.
The image sensor 510 is used to collect image data.
The storage device 530 stores program codes for implementing respective steps in the method for detecting dog nose print feature points according to the embodiment of the present invention.
The processor 530 is configured to run the program codes stored in the storage device 520 to execute the corresponding steps of the method for detecting dog nose print characteristic points according to the embodiment of the present invention, and is configured to implement the detection module 410 and the coordinate calculation module 420 in the device for detecting dog nose print characteristic points according to the embodiment of the present invention.
Furthermore, according to an embodiment of the present invention, there is also provided a storage medium on which program instructions are stored, which when executed by a computer or a processor are used to execute corresponding steps of the method for detecting dog nose print characteristic points according to an embodiment of the present invention, and are used to implement corresponding modules in the device for detecting dog nose print characteristic points according to an embodiment of the present invention. The storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a portable compact disc read only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer readable storage medium can be any combination of one or more computer readable storage media, e.g., one containing computer readable program code for randomly generating a sequence of action instructions and another containing computer readable program code for performing dog nose print feature point detection.
In one embodiment, the computer program instructions, when executed by a computer, may implement the functional modules of the apparatus for detecting dog nose print characteristic points according to the embodiment of the present invention, and/or may execute the method for detecting dog nose print characteristic points according to the embodiment of the present invention.
The modules in the detection system of the dog nose print characteristic point according to the embodiment of the present invention may be implemented by a processor of an electronic device for detecting the dog nose print characteristic point according to the embodiment of the present invention running computer program instructions stored in a memory, or may be implemented when computer instructions stored in a computer-readable storage medium of a computer program product according to the embodiment of the present invention are run by a computer.
According to the detection method, the device, the system and the storage medium of the dog nose print feature point, the coordinates of the dog nose print feature point are obtained through a simple detection method and model regression, the detection accuracy and the real-time performance of the dog nose print feature point can be effectively improved, and the operation efficiency is high.
Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the foregoing illustrative embodiments are merely exemplary and are not intended to limit the scope of the invention thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another device, or some features may be omitted, or not executed.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the method of the present invention should not be construed to reflect the intent: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where such features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some of the modules in an item analysis apparatus according to embodiments of the present invention. The present invention may also be embodied as apparatus programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
The above description is only for the specific embodiment of the present invention or the description thereof, and the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the protection scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for detecting dog nose print characteristic points is characterized by comprising the following steps:
obtaining the coordinate deviation of the dog nose print characteristic points in the dog nose image and the corresponding dog nose print reference characteristic points based on the dog nose image and the trained dog nose print model; wherein the training of the dog nose print model comprises:
marking characteristic points of the dog nose print in the dog nose print training sample image based on a preset rule, and obtaining coordinates of the corresponding reference characteristic points of the dog nose print;
calculating coordinate deviation between each characteristic point of the dog nose print in the marked dog nose print training sample image and the corresponding reference characteristic point of each dog nose print;
training the dog nose print model according to the marked dog nose print training sample image and the corresponding coordinate deviation to obtain a trained dog nose print model;
and obtaining the coordinates of the dog nose print characteristic points in the dog nose image according to the coordinates of the dog nose print reference characteristic points and the coordinate deviation.
2. The detection method according to claim 1, wherein the obtaining coordinates of the reference feature point of the corresponding dog nose print comprises: and averaging the coordinates of the same characteristic point of the dog nose print in the marked dog nose print training sample image to obtain the corresponding coordinates of the dog nose print reference characteristic point.
3. The detection method of claim 1, wherein the predetermined rule comprises feature point labeling based on at least one of a nostril contour and a nose contour of the nose of the dog.
4. The detection method of claim 3, wherein performing feature point labeling based on the nose contour of the dog nose comprises: marking the characteristic points of the junction of the vertical line of the dog nose center and the upper and lower side boundaries of the nose outline, and the characteristic points of the junction of the horizontal line of the dog nose center and the left and right side boundaries of the nose outline.
5. The detection method of claim 4, wherein feature point labeling based on the nose contour of the dog nose further comprises: and taking the feature points of intersection of the vertical line of the center of the dog nose, the horizontal line of the center of the dog nose and the boundary of the nose contour as a reference, and marking the feature points at equal intervals along the nose contour.
6. The detection method of claim 3, wherein performing feature point labeling based on the nostril contour of the dog's nose comprises: marking characteristic points of the junction of a left nostril center vertical line and the upper and lower side boundaries of the left nostril outline, and characteristic points of the junction of a left nostril center horizontal line and the left and right side boundaries of the left nostril outline; and
marking characteristic points of the junction of the right nostril center vertical line and the upper and lower side boundaries of the right nostril outline, and characteristic points of the junction of the right nostril center horizontal line and the left and right side boundaries of the right nostril outline.
7. The detection method of claim 6, wherein feature point labeling based on the nostril contour of the dog nose further comprises: marking characteristic points at equal intervals along the contour of the left nostril by taking the characteristic points of the intersection of the central vertical line of the left nostril and the central horizontal line of the left nostril and the contour of the left nostril as a reference; and
and taking the feature points of the intersection of the right nostril center vertical line and the right nostril center horizontal line with the right nostril outline as a reference, and marking the feature points at equal intervals along the right nostril outline.
8. A device for detecting a dog nose print feature point, the device comprising:
the detection module is used for obtaining the coordinate deviation of the dog nose print characteristic points in the dog nose image and the corresponding dog nose print reference characteristic points based on the dog nose image and the trained dog nose print model; wherein the training of the dog nose print model comprises:
marking characteristic points of the dog nose print in the dog nose print training sample image based on a preset rule, and obtaining coordinates of the corresponding reference characteristic points of the dog nose print;
calculating coordinate deviation between each characteristic point of the dog nose print in the marked dog nose print training sample image and the corresponding reference characteristic point of each dog nose print;
training the dog nose print model according to the marked dog nose print training sample image and the corresponding coordinate deviation to obtain a trained dog nose print model;
and the coordinate calculation module is used for obtaining the coordinates of the dog nose print characteristic points in the dog nose image according to the coordinates of the dog nose print reference characteristic points and the coordinate deviation.
9. A dog nose print feature point detection system comprising a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor when executing the computer program implements the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a computer, carries out the steps of the method according to any one of claims 1 to 7.
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| CN113420721B (en) * | 2021-07-21 | 2022-03-29 | 北京百度网讯科技有限公司 | Method and device for labeling key points of image |
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