Controller, computer-implemented method, computer program and non-volatile data carrier for selecting unique animal identity

Abstract

The camera (140) registers image data (Dimg) representing the individual (130), the image data (Dimg) being registered using predefined exposure and / or ISO settings (xs). The image data (Dimg) is matched to reference data (DR) in a reference database (160). A unique animal identity (ID1) of the set of animal identities is assigned to the individual (130) if the image data (Dimg) satisfies a matching criterion with respect to a particular data record associated with the unique animal identity (ID1). When at least one first frame of the image data (Dimg) is registered and a predefined exposure and / or ISO setting (xs) is used, at least one region of interest is defined by performing a search process in the image data (Dimg). It is checked in each region of interest whether a quality criterion is met, and if the quality criterion is not met, the camera (140) is controlled to adjust its exposure and / or ISO setting (xs') such that subsequently registered image data (Dimg) is estimated to meet the quality criterion.

Description

Technical Field

[0001] This invention relates generally to automated milking of dairy animals. In particular, it relates to the controller and corresponding computer-implemented method as described in the preamble of claim 1. The invention also relates to computer programs and non-volatile data carriers storing such computer programs. Background Technology

[0002] The modern dairy industry relies heavily on advanced technologies in milk processing and livestock management. Specifically, advanced image processing often plays a crucial role in cattle management today. Below are some examples of such solutions.

[0003] WO 2021 / 032890 discloses a rotary milking platform comprising multiple pens and an RFID animal identification system for identifying animals entering the pens on the platform. A microprocessor reads signals from an image capture device and calculates a feature vector based on a captured image of each animal. Multiple reference feature vectors are stored, each including a corresponding metric matrix derived from the image captured by the image capture device and cross-referenced with the identity of the corresponding animal. The microprocessor compares the calculated feature vector of each animal with the stored reference feature vectors until a best match is determined. The identity of the animal matching the reference feature vector is then determined as the identity of the animal with the calculated feature vector. The determined identity of the animal in the relevant pen is compared with the identity of the animal determined by the RFID system for that pen. In a favorable comparison, the identity of the animal determined based on the captured image of the animal is confirmed as the animal's identity. If a conflict is determined between the two identities, a conflict alarm signal is generated.

[0004] EP 4 187 505 describes a method and system for identifying an animal. The method includes the steps of: acquiring data associated with an animal moving through space via an animal recording module, the data including video from a two-dimensional imaging sensor; extracting a set of parameters from the data by performing the steps of: determining visual features of the animal based on the data; identifying instances in the data representing the shape of the animal to form detected instances; identifying a set of reference points in each of the detected instances; determining one or more characteristics of the animal by processing at least some of the identified reference points in a first module, the first module including a trained neural network; and generating multiple sets of parameters including the visual features and the determined one or more characteristics; based on... The generated multiple sets of parameters generate identifier vectors; a known identifier vector is selected from a first database of known identifier vectors, each known identifier vector corresponding to a unique registered animal; a list of matching scores is determined by comparing the generated identifier vectors with the selected known identifier vectors; in response to determining that at least one of the selected known identifier vectors has a matching score exceeding a threshold; a known identifier vector is selected from at least one of the known identifier vectors based on at least one criterion; the animal is associated using the selected known identifier vector; and the animal is identified as a unique registered animal of the selected known identifier vector; and in response to determining that no selected known identifier vector has a matching score exceeding a threshold, the animal is identified as unknown.

[0005] US 11,080,522 discloses a system and method for identifying individual animals based on images (such as 3D images) of animals, particularly cattle and dairy cows. Identifying individual animals can be complex when they live in areas or enclosures where they move freely. In a first aspect, this disclosure relates to a method for identifying individual animals within a group of animals with known identities, the method comprising the steps of: acquiring at least one image of the back of a preselected animal; extracting data from said at least one image relating to the anatomical structure and / or topological structure of the back of the preselected animal; and comparing and / or matching said extracted data with reference data corresponding to the anatomical structure and / or topological structure of the back of an animal with known identities, thereby identifying the preselected animal. This method and system can be used to monitor feed intake, such as feed intake in dairy cows, and health status.

[0006] Therefore, various image-based methods are known for identifying dairy animals in different milking-related situations. However, due to the large variations in color, hue, and / or fur characteristics between different individuals in an animal herd, ensuring that such image data is available for recording, and thus enabling reliable image-based identification, can be challenging. Summary of the Invention

[0007] Therefore, the object of the present invention is to provide a solution that alleviates the above-mentioned problems and thus allows for effective and reliable image-based identification of animals in a predefined set of animals.

[0008] According to one aspect of the invention, this objective is achieved by a controller for selecting a unique animal identity for an individual from a set of animal identities. The controller is configured to acquire image data representing at least one body part of an individual. The image data is registered using predefined exposure and / or ISO settings. Specifically, the controller is configured to control a camera to register at least one first frame of the image data using the predefined exposure and / or ISO settings, and to define at least one region of interest (ROI) within the at least one first frame of the image data. Here, each ROI contains a corresponding set of pixels from the at least one first frame of the image data, and the at least one ROI is defined by a search process. The controller is configured to perform a search process within the at least one first frame of the image data, the search process being configured to detect at least one image object satisfying at least one size-shape criterion, such as at least one size-shape criterion related to the contour of a body or its part; the length or length range of the body or its part; the width or width range of the body or its part; and / or the shape of the body part. The search process is performed in three-dimensional (3D) image data specifying the distance between the image sensor plane in the camera and the corresponding distance between different imaged surfaces represented by the image data. The controller is configured to define at least one region of interest (ROI) within at least one image object that satisfies at least one size-shape criterion. The controller is also configured to check whether a corresponding set of pixels within each ROI satisfies at least one quality criterion. If the corresponding set of pixels satisfies at least one quality criterion, the controller is further configured to match the acquired image data against reference data in a reference database containing a set of data records, each reflecting a corresponding visual characteristic of an individual within the set of animal identities. If only the acquired image data satisfies the matching criterion relative to a specific data record associated with a unique animal identity in the reference database, the controller is configured to assign a unique animal identity to the individual. However, if a corresponding set of pixels in at least one ROI does not satisfy at least one quality criterion, the controller is configured to control the camera to adjust its exposure and / or ISO settings such that image data registered after at least one first frame is estimated to satisfy at least one quality criterion. The controller is then configured to use the adjusted exposure and / or ISO settings to match subsequent image data with reference data in the reference database, the subsequent image data representing at least one body part and already registered after at least one first frame. If only subsequent image data meets the matching criteria for a specific data record associated with a unique animal identity in the reference database, the controller is configured to assign the unique animal identity to the individual.

[0009] The controller is advantageous because it automatically tunes the camera to capture high-quality image data of relevant animal body parts (e.g., eyes, ears, mouth, nose, head, and / or back), making it possible to identify animals in a convenient, direct, and reliable manner based on the image data.

[0010] According to one embodiment of this aspect of the invention, at least one first frame of image data comprises at least one two-dimensional image, and at least one quality standard defines a predefined range of light intensity levels, within which at least a threshold portion of pixels in a corresponding set of pixels in each of at least one region of interest must represent the light intensity level. Here, a controller is configured to examine a corresponding set of pixels in each of at least one region of interest against the predefined range of light intensity levels. If the threshold portion of pixels in a corresponding set of pixels in each of at least one region of interest does not represent a light intensity level within the predefined range, and pixels in at least one region of interest represent a light intensity level primarily below the predefined range, the controller is configured to control the camera to adjust its exposure and / or ISO settings to increase the light intensity of the image data registered after at least one first frame. Similarly, if the threshold portion of pixels in a corresponding set of pixels in each of at least one region of interest does not represent a light intensity level within the predefined range, and pixels in at least one region of interest represent a light intensity level primarily above the predefined range, the controller is alternatively configured to control the camera to adjust its exposure and / or ISO settings to decrease the light intensity of the image data registered after at least one first frame. Therefore, sufficient camera adjustments can be achieved with very low latency.

[0011] According to another embodiment of this aspect of the invention, checking a corresponding set of pixels in each of at least one region of interest against a predefined range of light intensity levels includes performing at least one statistical analysis of the light intensity levels represented by the corresponding set of pixels in each of the at least one region of interest. For example, the controller may be configured to calculate the mean, median, and / or standard deviation of the light intensity levels in each region of interest, and based thereon determine whether at least one quality criterion is met.

[0012] According to another embodiment of this aspect of the invention, at least one first frame of image data comprises at least one 3D image having range data of corresponding distances between an image sensor plane in a specified camera and different imaged surfaces represented by the image data. Here, at least one quality criterion defines a threshold granularity level that at least one first frame of image data must not exceed. Granularity represents the signal-to-noise ratio (SNR), where a high degree of granularity is equivalent to a relatively low SNR, and vice versa. In this embodiment of the invention, a controller is configured to examine a corresponding set of pixels in each region of interest against a threshold granularity level, and if the threshold granularity level is exceeded, the controller is configured to control the camera to adjust its exposure and / or ISO settings such that the granularity level is expected to decrease. This means that the controller is configured to increase a first parameter specifying the exposure time for the camera, increase a second parameter specifying the aperture value for the camera, and / or decrease a third parameter specifying the ISO value for the camera. Thus, the camera may be able to capture high-quality 3D image data of at least one body part already in the first frame the next time the considered animal interacts with the automated milking device.

[0013] According to another embodiment of this aspect of the invention, checking a corresponding set of pixels in each of at least one region of interest against a threshold granularity level includes performing at least one statistical analysis of the distances represented by the corresponding set of pixels in each of the at least one region of interest. Therefore, the controller may be configured, for example, to calculate the average, median, and / or standard deviation values ​​of the distance values ​​defined by the corresponding set of pixels in each of the at least one region of interest, and based on this, to determine whether at least one quality criterion is met.

[0014] According to another embodiment of this aspect of the invention, each data record in the reference database reflects the corresponding visual characteristics of a unique animal in the set of animal identities, the data record comprising: a 2D image of the animal or its parts; a 3D image of the animal or its parts; and / or a set of vectors reflecting surface and / or spatial relationships between multiple body points on the animal or its parts. Therefore, there is considerable flexibility in terms of the available matching processes to be employed.

[0015] Furthermore, according to one embodiment of this aspect of the invention, if the controller has already assigned a unique animal identity to an individual, the controller is configured to update a reference database relative to the data record associated with the unique identity, the update being based on acquired image data reflecting the individual to which the unique animal identity has been assigned. Thus, the reference data record can remain synchronized with any changes in the animal's visual characteristics (e.g., due to aging).

[0016] According to another embodiment of this aspect of the invention, to address situations where different regions of interest may require different adjustments to exposure and / or ISO settings, the controller is configured to perform a voting process. Here, the adjustment of exposure and / or ISO settings required by each region of interest is weighted by a centering factor defined within a predefined range, based on the distance between the corresponding center of the region of interest and the center of at least one first frame of the image data, and influences the exposure and / or ISO settings required by each region of interest in an inverse relationship with said distance. The controller is configured to count the votes from all regions of interest, each of which reflects the corresponding adjustment amount and direction weighted by the centering factor, and the controller is configured to determine, based on the majority decision of said votes, the adjustment of the exposure and / or ISO settings relative to their current settings, i.e., brighter or darker.

[0017] According to an embodiment of the invention constituting an alternative to the above-described embodiment, the regions of interest (ROIs) are organized into a first group of ROIs, a second group of ROIs, and a third group of ROIs, wherein the first group of ROIs is located in the central region of the image data, the second group of ROIs is located in the outer region surrounding the central region, and the third group of ROIs is located in the peripheral region surrounding the outer region. Here, the controller is configured to perform a voting process, wherein adjustments to exposure and / or ISO settings requested by each ROI in the central region are given a first weighting factor, adjustments to exposure and / or ISO settings requested by each ROI in the outer region are given a second weighting factor, and adjustments to exposure and / or ISO settings requested by each ROI in the peripheral region are given a third weighting factor, wherein the first weighting factor is greater than the second weighting factor, and the second weighting factor is greater than the third weighting factor. The controller is also configured to count votes from all ROIs, each vote reflecting a corresponding adjustment amount and direction, and to determine the amount and direction of adjustment of the exposure and / or ISO settings relative to their current settings based on the majority decision of the votes. Therefore, pixels located at the center of the frame have a greater impact on any adjustments to exposure and / or ISO settings compared to pixels located relatively far from the center of the frame (e.g., near the edge of the frame).

[0018] According to another aspect of the invention, this object is achieved by a computer-implemented method executed in a processing unit in a controller, which is then arranged to select a unique animal identity for an individual from a set of animal identities. The method includes: acquiring image data from a camera, the image data representing at least one body part of an individual, the image data being registered using predefined exposure and / or ISO settings; controlling the camera to register at least one first frame of the image data using the predefined exposure and / or ISO settings; defining at least one region of interest (ROI) in the at least one first frame of the image data, wherein each ROI comprises a corresponding set of pixels of the at least one first frame of the image data, and the at least one ROI is defined by: performing a search process in the at least one first frame of the image data, the search process being configured to detect at least one image object satisfying at least one size-shape criterion, and the search process being performed in three-dimensional image data of corresponding distances between an image sensor plane in a specified camera and different imaged surfaces represented by the image data, and defining at least one ROI satisfying the at least one size-shape criterion within the at least one image object; checking whether a corresponding set of pixels in each ROI of the at least one ROI satisfies at least one quality criterion, if the corresponding A set of pixels satisfies at least one quality criterion. The acquired image data is matched with reference data in a reference database, which includes a set of data records, each reflecting the corresponding visual characteristics of an individual within the set of animal identities. A unique animal identity is assigned to an individual if and only if the acquired image data satisfies the matching criteria relative to a specific data record associated with a unique animal identity in the reference database. If a corresponding set of pixels in at least one region of interest does not satisfy at least one quality criterion, the camera is controlled to adjust its exposure and / or ISO settings such that image data registered after at least one first frame is estimated to satisfy at least one quality criterion. Subsequent image data, representing at least one body part and registered after at least one first frame, is matched with reference data in the reference database using the adjusted exposure and / or ISO settings. If and only if the subsequent image data satisfies the matching criteria relative to a specific data record associated with a unique animal identity in the reference database, a unique animal identity is assigned to an individual. The advantages of this method and its preferred embodiments are apparent from the discussion of the system proposed in the foregoing reference.

[0019] According to another aspect of the invention, this objective is achieved by a computer program capable of being loaded into a non-volatile data carrier communicatively connected to a processing unit. The computer program includes software for executing the described method when the program is run on the processing unit.

[0020] According to another aspect of the invention, this objective is achieved by a non-volatile data carrier containing the aforementioned computer program.

[0021] Other advantages, beneficial features and applications of the invention will become apparent from the following description and dependent claims. Attached Figure Description

[0022] The invention will now be explained in more detail by way of preferred embodiments disclosed as examples and with reference to the accompanying drawings.

[0023] Figure 1 An identification device controllable by a controller according to one embodiment of the present invention is illustrated schematically;

[0024] Figures 2a to 2c This illustrates how different regions of interest can be defined in image data according to embodiments of the present invention;

[0025] Figures 3a to 3d Examples of quality standards related to the light intensity level range of image data according to embodiments of the present invention are illustrated; and

[0026] Figure 4 The general method according to the invention is illustrated by a flowchart. Detailed Implementation

[0027] Figure 1 A block diagram of an identification device, controllable by a controller 100, is shown according to one embodiment of the present invention. The controller 100 selects a unique animal identity for an individual from a set of animal identities.

[0028] The controller 100 is configured to acquire image data D from the camera 140. img The image data D img It contains at least one first frame, i.e., a still image, and the image data D img Represents at least one body part of individual 130, such as facial features, including eyes, ears, or mouth and nose, head, and / or back. Image data D img Registration is performed using predefined exposure and / or ISO settings (xs), which are preferably considered suitable for registering image data of the majority of individuals within a set of animal identities. img Exposure and / or ISO settings may include one or more of the following parameters for camera 140: a first parameter specifying the exposure time, a second parameter specifying the aperture value, and / or a third parameter specifying the ISO value.

[0029] The controller 100 is configured to transfer the acquired image data Dimg Matching is performed with reference data DR in reference database 160, which contains a set of data records, each reflecting a corresponding visual characteristic, such as facial features, like eyes, ears, or the snout, head, and / or back portion of an individual in the said set of animal identities. If only the acquired image data D is available... img If a matching criterion is met relative to a specific data record associated with a unique animal identity ID1 in the reference database 160, the controller 100 is configured to assign the unique animal identity ID1 to the individual 130.

[0030] According to one embodiment of the invention, if the controller 100 has already assigned a unique animal identification ID1 to an individual 130, i.e., if the matching criteria are met, the controller 100 is further configured to update a reference database 160 relative to the data record associated with the unique identification ID1, the update being based on the obtained image data D reflecting the individual 130 to which the unique animal identification ID1 has been assigned. img .

[0031] According to one embodiment of the invention, each data record in the reference database 160 reflects the corresponding visual characteristics of a unique animal in the set of animal identities. The data record includes: a 2D image of the animal or its parts; a 3D image of the animal or its parts; and / or a set of vectors reflecting surface and / or spatial relationships between multiple body points on the animal or its parts. Therefore, the controller 100 determines which matching process to use to determine the acquired image data D. img There is great flexibility in terms of whether the matching criteria are met.

[0032] According to the present invention, the controller 100 is specifically configured to control the camera 140 to register image data D using predefined exposure and / or ISO settings xs. img At least one first frame. Now also referencing... Figures 2a to 2c The controller 100 is also configured to process image data D img At least one region of interest (ROI) is defined in at least one first frame: ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and / or ROI12. Each ROI includes image data D. img At least one corresponding set of pixels in the first frame, and at least one region of interest defined by a search process. In image data D img The search process is performed in at least one first frame. The search process is configured to detect at least one image object that meets at least one size-shape criterion. The search process is performed in the image sensor plane of the designated camera 140 and by the image data D.img This is performed in 3D image data representing the corresponding distances between different imaged surfaces, i.e., surface elements capable of reflecting electromagnetic radiation, such as light waves. The controller 100 is configured to define corresponding regions of interest (ROIs) ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and / or ROI12 within at least one image object satisfying at least one size-shape criterion. This means that TOF camera data can be used to register image data D. img Alternatively, 2D image data supplemented with distance data can be used, such as image data determined via laser measurement or stereo imaging.

[0033] In each of at least one region of interest (ROI) ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and / or ROI12, controller 100 is configured to check whether a corresponding set of pixels meets at least one quality criterion. As will be discussed below, at least one quality criterion may, for example, relate to the light intensity level represented by pixels and / or the SNR (signal-to-noise ratio) of the image data. If a corresponding set of pixels in at least one of the at least one ROI ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and / or ROI12 does not meet at least one quality criterion, then controller 100 is configured to control camera 140 to adjust its exposure and / or ISO settings such that the image data D registered after at least one first frame... img It is estimated to meet at least one quality standard. As will be described in detail below, adjusting the exposure and / or ISO settings may include changing said settings such that the image data D img Increased light intensity in the image data D img The light intensity in the image decreases, or the image data D img The granularity is reduced.

[0034] If camera 140 is controlled to adjust its exposure and / or ISO setting xs', controller 100 is also configured to transfer subsequent image data D img The subsequent image data D is matched with the reference data DR in reference database 160. img This represents at least one body part 132, 133, 134, 135, 136, 137, 138, and / or 139, and has been registered after at least one first frame using adjusted exposure and / or ISO settings xs'. If only subsequent image data D... imgThe matching criteria are met relative to a specific data record associated with a unique animal identity ID1 in reference database 160. Controller 100 is configured to assign the unique animal identity ID1 to individual 130.

[0035] Exposure and / or ISO settings ID1:xs1 affect the image data D generated by the image sensor array in camera 140. img The brightness. Exposure and / or ISO setting ID1:xs1 may contain one or more of three variable parameters, where the exposure time of camera 140 represents the first parameter. The aperture value represents the second parameter. Exposure time and aperture value are similar to each other because they both determine the amount of light reaching the image sensor array in camera 140. The amount of light reaching the image sensor array can be increased by increasing the exposure time or increasing the aperture value, or both.

[0036] For example, each photodetector in an image sensor array can generate a voltage proportional to the amount of light striking the photodetector. Therefore, an overall increase in the amount of light results in a higher voltage output from the photodetectors in the image sensor array.

[0037] Change image data D img Another way to adjust brightness is by modifying the camera's so-called ISO (International Organization for Standardization) setting. Therefore, the ISO value is the third of the three variable parameters. The ISO value is a mapping that indicates the brightness of the resulting image that the image sensor array should give in terms of exposure time and aperture value for a particular exposure setting. Slightly simplified, the ISO value can be viewed as the image data D... img The offset level of dynamic range between full black and full white. Increasing the ISO value shifts the entire dynamic range upward toward white, while decreasing the ISO value shifts the entire dynamic range downward toward black.

[0038] Each of the parameters—exposure time, aperture value, and ISO value—has its own specific advantages and disadvantages. While a longer exposure time is advantageous because it increases the amount of light reaching the image sensor array, it is disadvantageous because it risks causing motion artifacts in the form of blur. An increased aperture value is advantageous because it also increases the amount of light reaching the image sensor array. However, the larger the aperture value, the shallower the depth of field. That is, with a large aperture value, only objects within a very short distance from the camera will be in focus. Compared to the other two parameters, changes in the ISO value do not affect the amount of light reaching the image sensor array. Each image sensor array has a so-called base ISO value, which represents the technically optimal mapping of light read from the image sensor array to image data. Typically, the base ISO value represents the minimum recommended ISO value for a given image sensor array. Any ISO value higher than the base ISO value will make the image data brighter, but at the cost of reduced dynamic range, potentially even overexposure / cropping in highlights, and a decreased signal-to-noise ratio (SNR), which typically manifests as increased graininess in the image data. In other words, the higher the ISO value, the higher the light intensity and the lower the SNR of the image data.

[0039] Figure 2a An example of how image data D can be processed according to one embodiment of the present invention is illustrated. img Different regions of interest (ROIs) are defined in the image data D. Here, image data D... img This represents a front view of the head / face of individual 130. This type of image data is D. img A single camera 140 can be positioned directly in front of the individual, for example, in the entrance passage of a rotating milking platform. Alternatively, two or more cameras 140 can be arranged on separate sides of such a passage or similar pathway, the two or more cameras 140 being adapted to capture image data D of the individual 130 at corresponding angles. img For example, if / when an individual might respond to some trigger to rotate its head to one side or the other. According to embodiments of the invention, at least one camera may also be positioned at the milking point, i.e., where the animal is milked. Again, here, at least one camera may be positioned above, in front of, and / or above the animal. If two or more cameras 140 are used, each of the cameras preferably has a separate set of exposure and / or ISO settings ID1:xs1 stored in data memory 120 for each unique animal identity.

[0040] According to an embodiment of the present invention, image data D for defining the region of interest is provided. imgSize-shape criteria can involve: the outline of a body or its parts; the length or length range of a body or its parts; the width or width range of a body or its parts; and / or the shape of a body part. Therefore, for example, a search process can detect, for instance, the shape of a body part. Figure 2a The examples given are eyes 132, ears 133 and 134, and mouth and nose 135, such as Figure 2b The head 136 and / or neck portion 138 of the individual 130 illustrated in the example, and / or as... Figure 2c The example illustrates the back portion 137 and / or the spine portion 139.

[0041] When registering image data D img In at least one first frame, it is assumed that the camera 140 has a positioning and field of view relative to the individual 130 such that at least one body part 132, 133, 134, 135, 136, 137, 138, and / or 139 is located near the center C of the still image frame. Therefore, it is generally preferred that pixels located at the center of the frame have a greater influence on any adjustments to exposure and / or ISO settings than pixels located relatively far from the frame center (e.g., pixels near the edge of the still image frame). Furthermore, image data D... img At least one body part 132, 133, 134, 135, 136, 137, 138 and / or 139 depicted may have very different skin / fur colors / hues. For example, one or more illuminators on camera 140 may emit infrared (IR) light toward at least one body part. Depending on the spatial relationship between the illuminators, camera 140 and at least one body part 132, 133, 134, 135, 136, 137, 138 and / or 139, different body parts or portions thereof may not be adequately illuminated by IR light.

[0042] As discussed above, in order to mitigate this problem, the controller 100 is configured to check whether a corresponding set of pixels in each of the regions of interest (ROIs) ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12 meets at least one quality criterion, for example, related to the light intensity level represented by the pixels in the corresponding set of pixels in each of the regions of interest and / or the SNR of the image data in each of the regions of interest.

[0043] In some cases, the light conditions and / or light reflection characteristics of at least one body part 132, 133, 134, 135, 136, 137, 138 and / or 139 can be obtained from image data D. imgThe exposure changes substantially throughout at least one first frame. For example, pixels in one or more regions of interest may be underexposed, while pixels in one or more other regions of interest may be overexposed. In such cases, it is preferable to assign different weights to the regions of interest based on their respective distances from the center of the frame. (Reference) Figure 2a To address situations where pixel values ​​in some regions of interest indicate that light intensity should be increased while pixel values ​​in other regions of interest indicate that light intensity should be decreased, the controller 100 can perform a voting process, where adjustments to the exposure and / or ISO settings required for each region of interest are weighted by a centering factor. The centering factor is defined within a predefined range, such as between 1 and 5, and is based on the corresponding center of the region of interest and image data D. img The distance between at least one center C of the first frame. The centering factor affects the exposure and / or ISO settings required by each region of interest (ROI) in an inverse relationship with said distance, such that the ROI 3 located at the center receives the maximum centering factor, for example, 5, and other ROIs located elsewhere receive lower centering factors, which decrease as the distance to the center C increases.

[0044] For example, in Figure 2a In the diagram, the center C1 of region of interest ROI1 is located at a distance d1 from the center C, and the center C6 of region of interest ROI6 is located at a distance d6 from the center C, where d6 is 2.5 times d1. Therefore, if region of interest ROI1 has a centering factor of 3.5, then region of interest ROI6 can have a centering factor of 1.5.

[0045] The controller 100 is configured to count votes from all regions of interest, each of which reflects a corresponding amount and direction of adjustment, i.e., brighter or darker, weighted by a corresponding centralization factor, and to determine the amount and direction of adjustment of the exposure and / or ISO settings relative to their current settings based on the majority decision of the votes.

[0046] Now for reference Figure 2b and Figure 2c According to an alternative embodiment of the invention, regions of interest ROI7, ROI8, RO9, ROI10, and ROI11 are instead organized into a first group of regions of interest, a second group of regions of interest, and a third group of regions of interest, wherein the first group of regions of interest ROI7 and ROI11 are located in image data D. img In the central region 203, the second set of regions of interest ROI8 and ROI10 are located in the outer region 202 surrounding the first region 203, and the third set of regions of interest ROI9 is ​​located in the peripheral region 201 surrounding the outer region 202.

[0047] Similar to the above, the adjustments required by the region of interest are transferred from them to the image data D. img The corresponding distance weighting is applied to the center C of at least one first frame. Here, adjustments requested by each region of interest in the central region 203 are given a first weighting factor, adjustments requested by each region of interest in the outer region 202 are given a second weighting factor, and adjustments requested by each region of interest in the peripheral region 201 are given a third weighting factor, wherein the first weighting factor is greater than the second weighting factor, and the second weighting factor is greater than the third weighting factor. For example, the first weighting factor can be 3, the second weighting factor can be 2, and the third weighting factor can be 1. However, of course, any other specific weighting factor is equally conceivable, provided that they have the relative proportions indicated above. The controller 100 counts the votes from all regions of interest, each of which reflects the corresponding adjustment amount and direction, i.e., upward or downward light intensity. Similarly, the majority decision determines the final adjustment of the exposure and / or ISO settings relative to their current settings in terms of amount and direction.

[0048] Now for reference Figures 3a to 3d According to one embodiment of the present invention, image data D img At least one first frame contains one or more 2D images. Here, at least one quality criterion defines a predefined range R of light intensity level I, within which at least a threshold portion of pixels in a corresponding set of pixels in each of the regions ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12 must respectively represent a light intensity level that satisfies the quality criterion. To test the quality criterion, controller 100 is configured to examine a corresponding set of pixels in each of the at least one region ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12 against the predefined range R of light intensity level I.

[0049] If the threshold portion of a pixel in a corresponding set of pixels in each region of interest does not represent a light intensity level in a predefined range R, the controller 100 is further configured to determine whether a pixel in the region of interest represents a light intensity level I that is primarily below or above the predefined range R. Figure 3a An example is shown where histogram 410 represents a light intensity level I that is primarily below a predefined range R, and Figure 3b An example is shown in which histogram 420 represents a light intensity level I that is primarily above a predefined range R.

[0050] Figure 3c A monochrome example of histogram 430 is shown, which represents the light intensity level I mainly within a predefined range R, i.e., where no adjustment of the camera 140's exposure or ISO settings is required. Figure 3d It shows the corresponding Figure 3c The example in the example, however, shows that the three individual histograms 341, 342 and 343 respectively reflect the corresponding color channels, such as red, green and blue, and histogram 340 reflects the combined channel, wherein all channels in the combined channel represent the light intensity level I mainly within a predefined range R.

[0051] If the pixels in the regions of interest ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12 respectively represent light intensity levels I that are primarily below a predefined range R, then the controller 100 is configured to control the camera 140 to adjust its exposure and / or ISO settings to increase the image data D registered after at least one first frame. img The light intensity. In practice, this may include increasing one or more of the following parameters of the camera 140: a first parameter specifying the exposure time, a second parameter specifying the aperture value, and / or a third parameter specifying the ISO value.

[0052] If the pixels in the regions of interest ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12 respectively represent light intensity levels I that are primarily above a predefined range R, then the controller 100 is configured to control the camera 140 to adjust its exposure and / or ISO settings to reduce the image data D registered after at least one first frame. img The light intensity. In practice, this may include reducing one or more of the first, second, and / or third parameters of the camera 140.

[0053] Naturally, the check of the threshold portion of the pixels in the corresponding set of pixels in each region of interest against the light intensity level in the predefined range R can also include the voting process described above.

[0054] Furthermore, checking whether a corresponding set of pixels in each of the regions of interest (ROIs) ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12 meets a quality standard related to a predefined range R of light intensity level I preferably includes performing at least one statistical analysis on the light intensity level I represented by a corresponding set of pixels in each of the ROIs. Therefore, the controller 100 can be configured to calculate the mean, median, and / or standard deviation values ​​of the light intensity level in each ROI and determine whether at least one quality standard is met. If, for example, one or more ROIs contain pixel values ​​with a light intensity level I, which is related to the image data D... img It may be advantageous if the light intensity level I represented by pixels in at least one other region of interest in the first frame is substantially different. That is, thus, regions of interest representing outlier data can be given less weight or ignored entirely, rather than risking making the image data D... img The risk of data quality degradation in the remaining regions of interest.

[0055] As mentioned above, according to embodiments of the present invention, other quality standards may also be used as alternatives to or in combination with the quality standards described above.

[0056] In addition to 2D image data, or as a substitute for 2D image data, image data D img At least one first frame may contain at least one 3D image, the at least one 3D image having an image sensor plane in a designated camera 140 and an image data D img This represents the range of distances between different imaged surfaces. In this case, at least one quality standard defines the image data D. img At least one first frame must not exceed a threshold granularity level. The granularity level is then typically related to the image data D. img The SNR is related to this. This could mean, for example, that an SNR below a certain value is equivalent to a granularity level above a threshold level.

[0057] Here, the controller 100 is configured to examine a corresponding set of pixels in each of the regions of interest (ROIs) ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12 for a threshold granularity level.

[0058] If the threshold granularity is exceeded, i.e., if the SNR drops below a certain value, the controller 100 is configured to control the camera 140 to adjust its exposure and / or ISO settings, such that the image data D registered after at least one first frame... img It is estimated to meet the quality standards. To this end, the controller 100 may increase a first parameter of the exposure time of the specified camera 140, increase a second parameter of the aperture value of the specified camera 140, and / or decrease a third parameter of the ISO value of the specified camera 140.

[0059] According to one embodiment of the invention, the controller 100 is configured to examine a corresponding set of pixels in the regions of interest against a threshold granularity by performing at least one statistical analysis on the distances represented by a corresponding set of pixels in each of the regions of interest (ROIs) ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11, and ROI12. Therefore, the controller 100 may be configured to calculate the average, median, and / or standard deviation of the distance values ​​defined by a corresponding set of pixels in each of the at least one regions of interest, and based on this, determine whether a granularity level has been exceeded.

[0060] Similar to the above, the controller can perform a voting process to resolve pixel values ​​in some regions of interest that exceed the granularity level and are within the same image data D. img The pixel values ​​in some other regions of interest indicate cases where the granularity level is not exceeded.

[0061] It is generally advantageous that the controller 100 is configured to perform the above-described processes automatically by executing a computer program. Thus, the controller 100 may include a memory unit 105 (i.e., a non-volatile data carrier) storing a computer program 103, which in turn includes software for causing processing circuitry in the controller 100, in the form of at least one processor 101, to perform the actions mentioned in this disclosure when the computer program 103 is run on at least one processor 101.

[0062] For the purpose of summarizing and reference Figure 4 The flowchart in the diagram will now be used to describe a computer-implemented method according to the present invention, which is executed in at least one processor 101 of the controller 100.

[0063] In the first step 410, it is checked whether there is a person in front of the camera (e.g., at the entrance channel of the rotating milking platform or at the milking robot). If so, step 420 is executed; otherwise, the process loops back to and remains at step 410.

[0064] In step 420, at least one first frame of image data is registered by the camera, the image data representing at least one body part of the individual. The image data is registered using predefined exposure and / or ISO settings, which are preferably considered suitable for registering image data of most individuals in a group of animal identities to be identified.

[0065] Then, in step 430, it is checked whether at least one quality criterion is met. The check includes defining at least one region of interest (ROI) in at least one first frame of image data, wherein each ROI comprises a corresponding set of pixels from at least one first frame of image data. The at least one ROI is then defined by performing a search procedure in at least one first frame of image data, configured to detect at least one image object that satisfies at least one size-shape criterion. The search procedure is performed in 3D image data specifying the distances between the image sensor plane in a camera and the different imaged surfaces represented by the image data. At least one ROI is defined within the at least one image object that satisfies the at least one size-shape criterion. Finally, in each ROI, it is checked whether the corresponding set of pixels satisfies at least one quality criterion, such as those related to brightness and / or graininess / SNR as discussed above.

[0066] If a corresponding set of pixels in each region of interest in at least one region of interest meets at least one quality criterion, the predefined exposure and / or ISO settings remain unchanged, and then step 460 follows.

[0067] If a corresponding set of pixels in at least one region of interest fails to meet at least one quality criterion because the set of pixels is too dark and / or too grainy, the process continues to step 440.

[0068] If a corresponding set of pixels in at least one region of interest fails to meet at least one quality criterion because the set of pixels is too bright and / or too grainy, the process continues to step 450.

[0069] In step 440, the camera is controlled to adjust its exposure and / or ISO settings such that the image data registered after at least one first frame will be brighter and / or less noisy, and thus estimated to meet at least one quality criterion. The process then continues to step 460.

[0070] In step 450, the camera is controlled to adjust its exposure and / or ISO settings such that the image data registered after at least one first frame will be darker and / or less noisy, and thus estimated to meet at least one quality criterion. The process then continues to step 460.

[0071] In step 460, the image data is registered using the stored exposure and / or ISO settings (i.e., predefined exposure and / or ISO settings, exposure and / or ISO settings generated in step 440, or exposure and / or ISO settings generated in step 450).

[0072] The next step, 480, checks whether the image data registered in step 460 meets the matching criteria relative to a specific data record in the reference database. If so, the next step is 490, where a unique animal identity is assigned to the individual imaged in steps 420 and 460.

[0073] Otherwise, the process loops directly from step 480 back to step 410.

[0074] refer to Figure 4 The described processing steps can be controlled by a programmable processor. Furthermore, although the embodiments of the invention described above with reference to the accompanying drawings include a processor and processing executed in at least one processor, the invention is therefore extended to computer programs suitable for practicing the invention, particularly computer programs on or within a carrier. The program can be in the form of source code, object code, intermediate source code, and object code such as partially compiled form, or any other form suitable for use in a specific implementation of the process according to the invention. The program can be part of an operating system or a separate application. The carrier can be any entity or device capable of carrying the program. For example, the carrier can include storage media such as flash memory, ROM (read-only memory), such as DVD (Digital Video / Universal Disc), CD (Compact Disc), or semiconductor ROM, EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), or magnetic recording media such as floppy disks or hard disks. Furthermore, the carrier can be a transmissible carrier, such as electrical or optical signals, which can be transmitted via cables or optical fibers, or through radio components or other components. When the program is embodied in a signal, the signal can be transmitted directly via a cable or other device or component, and the carrier can be constituted by such a cable or device or component. Alternatively, the carrier may be an integrated circuit in which a program is embedded, the integrated circuit being adapted to perform related processing or to perform related processing.

[0075] By studying the accompanying drawings, the disclosure, and the appended claims, those skilled in the art can understand and implement variations of the disclosed embodiments when practicing the claimed invention.

[0076] When used in this specification, the term "comprising" is used to specify the presence of a stated feature, integer, step, or component. This term does not exclude the presence or addition of one or more additional elements, features, integers, steps, or components, or groups thereof. The indefinite article "a" does not exclude a plurality. In the claims, the word "or" should not be interpreted as an exclusive OR (sometimes referred to as "XOR"). Rather, expressions such as "A or B" cover all cases of "A and not B", "B and not A", and "A and B", unless otherwise indicated. The fact that certain measures are recited in mutually different dependent claims does not imply that combinations of these measures cannot be advantageously used. Any reference marks in the claims should not be interpreted as limiting the scope.

[0077] It should also be noted that the features from the various implementation schemes described herein can be freely combined unless it is explicitly stated that such a combination would be unsuitable.

[0078] The present invention is not limited to the embodiments described in the accompanying drawings, but can be freely varied within the scope of the claims.

Claims

1. A controller (100) for selecting a unique animal identity for an individual from a set of animal identities, said controller (100) being configured to: Image data (D) is obtained from the camera (140). img The image data (D) img The image data (D) represents at least one body part (132, 133, 134, 135, 136, 137, 138, 139) of an individual (130). img It is registered using predefined exposure and / or ISO settings (xs); The camera (140) is controlled to register the image data (D) using the predefined exposure and / or ISO settings (xs). img At least one first frame; In the image data (D img At least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) is defined in at least one first frame, wherein each region of interest within the at least one region of interest includes the image data (D). img The at least one set of pixels in the first frame, and the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) are defined as follows: In the image data (D img The search process is performed in at least one first frame of the image sensor plane (540) of the camera (140) and is configured to detect at least one image object that meets at least one size-shape criterion, and the search process is performed in conjunction with the image data (D) of the image sensor plane (540) of the camera (140). img The execution is performed in the three-dimensional image data representing the corresponding distances between the different imaged surfaces; as well as Define the at least one region of interest within the at least one image object that satisfies the at least one size-shape criterion; In each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11), check whether the corresponding set of pixels meets at least one quality standard. If the corresponding set of pixels meets at least one of the quality criteria. The obtained image data (D) img The image data (DR) is matched with reference data (DR) in a reference database (160) comprising a set of data records, each reflecting the corresponding visual characteristics of an individual in the set of animal identities, and if only the acquired image data (DR) is matched. img The data records must meet the matching criteria relative to a unique animal identity (ID1) in the reference database (160). Assign the unique animal identity (ID1) to the individual (130), and If a corresponding set of pixels in at least one of the at least one regions of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) does not meet the at least one quality criterion, The camera (140) is controlled to adjust its exposure and / or ISO settings (xs') so that image data (D) registered after the at least one first frame... img It is estimated to meet at least one of the quality criteria; Use the adjusted exposure and / or ISO settings (xs') to process subsequent image data (D img The subsequent image data (D) is matched with the reference data (DR) in the reference database (160). img ) represents the at least one body part (132, 133, 134, 135, 136, 137, 138, 139) and has been registered after the at least one first frame, and if and only the subsequent image data (D) img The matching criteria are satisfied relative to a specific data record associated with a unique animal identity (ID1) in the reference database (160). The unique animal identity (ID1) is assigned to the individual (130).

2. The controller (100) according to claim 1, wherein the image data (D) img The at least one first frame of the at least one quality criterion defines a predefined range (R) of light intensity level (I), within which at least a threshold portion of the pixels in the corresponding set of pixels in each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) must represent the light intensity level, and the controller (100) is configured to: The corresponding set of pixels in each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) are examined against the predefined range (R) of the light intensity level (I). If the threshold portion of the pixel in the corresponding set of pixels in each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) does not represent the light intensity level in the predefined range (R), and the pixel in at least one region of interest in the at least one region of interest represents a light intensity level (I) that is primarily lower than (410) the predefined range (R). The camera (140) is controlled to adjust its exposure and / or ISO settings (xs') to increase the image data (D) registered after the at least one first frame. img The light intensity, and If the threshold portion of the pixel in the corresponding set of pixels in each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) does not represent the light intensity level in the predefined range (R), and the pixel in at least one region of interest in the at least one region of interest represents a light intensity level (I) that is primarily higher than (420) the predefined range (R). The camera (140) is controlled to adjust its exposure and / or ISO settings (xs') to reduce the image data (D) registered after the at least one first frame. img The light intensity of the light.

3. The controller (100) of claim 2, wherein the examination of the corresponding set of pixels in each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) against the predefined range (R) of the light intensity level (I) comprises performing at least one statistical analysis of the light intensity level (I) represented by the corresponding set of pixels in each of the at least one region of interest.

4. The controller (100) according to any one of the preceding claims, wherein the image data (D) img The at least one first frame of the image sensor (540) comprises at least one three-dimensional image having range data, the range data specifying the image sensor plane (540) in the camera (140) and the image data (D) img The image data (D) represents the corresponding distance between different imaged surfaces, and the at least one quality criterion defines the image data. img The threshold granularity level that the at least one first frame must not exceed, and the controller (100) is configured to: The corresponding set of pixels in each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) is examined against the threshold granularity level, and if it exceeds the threshold granularity level; Control the camera (140) to adjust its exposure and / or ISO settings (xs') such that a first parameter specifying the exposure time of the camera (140) increases, a second parameter specifying the aperture value of the camera (140) increases, and / or a third parameter specifying the ISO value of the camera (140) decreases.

5. The controller (100) of claim 4, wherein the inspection of the corresponding set of pixels in each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) against the threshold granularity comprises performing at least one statistical analysis on the distance represented by the corresponding set of pixels in each of the at least one region of interest.

6. The controller (100) according to any one of the preceding claims, wherein each data record in the reference database (160) reflects the corresponding visual characteristics of a unique animal in the set of animal identities, the data record comprising at least one of the following: Two-dimensional images of animals or their parts. Three-dimensional images of animals or their parts and A set of vectors that reflect the surface and / or spatial relationships between multiple body points on an animal or its parts.

7. The controller (100) according to any one of the preceding claims, wherein the image data (D) is... img The at least one body part represented by ) includes at least one of the individual's (130) eyes (132), ears (133, 134), mouth and nose (135), head (136), back portion (137), neck region (138), and spine region (139).

8. A controller (100) according to any one of the preceding claims, wherein if the controller (100) has assigned the unique animal identity (ID1) to the individual (130), the controller (100) is further configured to update the reference database (160) relative to the data record associated with the unique identity (ID1), the update being based on obtained image data (D) reflecting the individual (130) to which the unique animal identity (ID1) has been assigned. img ).

9. The controller (100) according to any one of the preceding claims, wherein the exposure and / or ISO settings include at least one of the following parameters for the camera (140): The first parameter that specifies the exposure time. The second parameter that specifies the aperture value, and The third parameter that specifies the ISO value.

10. The controller (100) according to any one of the preceding claims, wherein the at least one size-shape criterion relates to at least one of the following: The outline of the body or its parts; The length or range of length of the body or its parts; The width or width range of the body or its parts; and The shape of body parts.

11. The controller (100) according to any one of the preceding claims, wherein the controller (100) is configured to: A voting process is performed, wherein the adjustments to the exposure and / or ISO settings required for each region of interest are weighted by a centering factor defined within a predefined range, based on the corresponding center (C1; C6) of the region of interest (ROI1; ROI6) and the image data (D). img The distance (d1, d6) between the centers (C) of at least one first frame, and the exposure and / or ISO settings required by each region of interest (ROI1; ROI6) are influenced by a relationship inversely proportional to the distance (d1, d6). Votes from all regions of interest are counted, each vote reflecting a corresponding adjustment amount and direction weighted by the centralization factor, and The majority decision of the vote determines the adjustment of the exposure and / or ISO settings in terms of quantity and direction relative to their current settings.

12. The controller (100) according to any one of claims 1 to 10, wherein the regions of interest (ROI7, ROI8, ROI9, ROI10, ROI11) are organized into a first group of regions of interest, a second group of regions of interest, and a third group of regions of interest, wherein the first group of regions of interest (ROI7, ROI11) is located within the image data (D). img In the central region (203) of the first region (203), the second set of regions of interest (ROI8, ROI10) is located in the outer region (202) surrounding the first region (203), and the third set of regions of interest (ROI9) is located in the peripheral region (201) surrounding the outer region (202), and the controller (100) is configured to: A voting process is conducted in which the adjustment of the exposure and / or ISO settings required by each region of interest in the central region (203) is given a first weighting factor, the adjustment of the exposure and / or ISO settings required by each region of interest in the outer region (202) is given a second weighting factor, and the adjustment of the exposure and / or ISO settings required by each region of interest in the peripheral region (201) is given a third weighting factor, wherein the first weighting factor is greater than the second weighting factor, and the second weighting factor is greater than the third weighting factor; Votes from all regions of interest are counted, each vote reflecting a corresponding adjustment amount and direction weighted by the weighting factor, and The majority decision of the vote determines the adjustment of the exposure and / or ISO settings in terms of quantity and direction relative to their current settings.

13. A computer-implemented method for selecting a unique animal identity for an individual from a set of animal identities, the method being executed in a processing unit (101) within a controller (100), and the method comprising: Image data (D) is obtained from the camera (140). img The image data (D) img The image data (D) represents at least one body part (132, 133, 134, 135, 136, 137, 138, 139) of an individual (130). img It is registered using predefined exposure and / or ISO settings (xs); The camera (140) is controlled to register the image data (D) using the predefined exposure and / or ISO settings (xs). img At least one first frame; In the image data (D img At least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) is defined in at least one first frame, wherein each region of interest within the at least one region of interest includes the image data (D). img The at least one set of pixels in the first frame, and the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) are defined as follows: In the image data (D img The search process is performed in at least one first frame of the image sensor plane (540) of the camera (140) and is configured to detect at least one image object that meets at least one size-shape criterion, and the search process is performed in conjunction with the image data (D) of the image sensor plane (540) of the camera (140). img The execution is performed in the three-dimensional image data representing the corresponding distances between the different imaged surfaces; as well as Define the at least one region of interest within the at least one image object that satisfies the at least one size-shape criterion; In each of the at least one region of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11), check whether the corresponding set of pixels meets at least one quality standard. If the corresponding set of pixels meets at least one of the quality criteria. The obtained image data (D) img The image data (DR) is matched with reference data (DR) in a reference database (160) comprising a set of data records, each reflecting the corresponding visual characteristics of an individual in the set of animal identities, and if only the acquired image data (DR) is matched. img The data records must meet the matching criteria relative to a unique animal identity (ID1) in the reference database (160). Assign the unique animal identity (ID1) to the individual (130), and If a corresponding set of pixels in at least one of the at least one regions of interest (ROI1, ROI2, ROI3, ROI4, ROI5, ROI6, ROI7, ROI8, ROI9, ROI10, ROI11) does not meet the at least one quality criterion, The camera (140) is controlled to adjust its exposure and / or ISO settings (xs') so that image data (D) registered after the at least one first frame... img It is estimated to meet at least one of the quality criteria; Use the adjusted exposure and / or ISO settings (xs') to process subsequent image data (D img The subsequent image data (D) is matched with the reference data (DR) in the reference database (160). img ) represents the at least one body part (132, 133, 134, 135, 136, 137, 138, 139) and has been registered after the at least one first frame, and if and only the subsequent image data (D) img The matching criteria are satisfied relative to a specific data record associated with a unique animal identity (ID1) in the reference database (160). The unique animal identity (ID1) is assigned to the individual (130).

14. A computer program (103) capable of being loaded into a non-volatile data carrier (105) communicatively connected to a processing unit (101), the computer program (103) comprising software for executing the method according to claim 14 when the computer program (103) is run on the processing unit (101).

15. A non-volatile data carrier (105) comprising the computer program (103) according to claim 14.

Images