TW202347172A - Animal growth identification method and system - Google Patents

Abstract

The invention relates to an animal growth identification method and system. At least one photographing unit is used for shooting an animal in a breeding area, and a captured stereoscopic image and a captured thermal image are transmitted to a control unit. A stereoscopic contour and a thermal image contour of the breeding animal are constructed in the control unit, respectively. Then the two contours are correspondingly superimposed to obtain the corrected contour of the animal, and then the volume of the corrected contour is calculated, and the conditional factors such as the breed and growth stage of the animal are identified to output the corresponding volume-to-weight conversion ratio. The obtained volume is then substituted into the volume-to-weight conversion ratio to obtain the weight of the animal. In this way, the weight of several animals in the breeding area can be summed up to accurately estimate the harvesting time of the animals in the breeding area, so as to achieve benefits such as effective savings in feed costs.

Description

Animal growth identification method and system

The present invention relates to an animal growth identification method and its system, and in particular, to a method and its system that can accurately predict the harvesting time of farmed animals to effectively save feed costs.

According to reports, farmed animals such as chickens, pigs, and cattle are the main sources of meat and protein in people’s daily diet. They not only have high nutritional value, but are also raw materials for many processed foods.

The weight monitoring of farmed animals in existing farms mainly relies on manual sampling and weighing of small numbers, or the use of fixed physical scales, allowing the animals to jump on and weigh themselves. However, whether it is manual sampling and weighing, or the animals weigh themselves, The measurement method of weighing on the scale has too little measurement frequency and too little data, which can easily lead to inaccurate estimates of group weight distribution. The feed cost of farmed animals generally accounts for more than 70% of the total operating costs. Therefore, the weight data of farmed animals is extremely important for farming operations. It can be used to calculate the optimal number of feed feeding days. In addition, weight distribution is also the main basis for calculating revenue. If the growth and harvest time of animals can be accurately estimated, it will help optimize feed costs and increase farmers' profits.

The reason is that in view of the above-mentioned shortcomings in the implementation of the existing methods of obtaining the weight of farmed animals, the inventor used his many years of manufacturing and design experience and knowledge in related fields to create the present invention through many ingenious efforts. .

The present invention relates to an animal growth identification method and its system. Its main purpose is to provide a method and its system that can accurately predict the harvest time of farmed animals to effectively save feed costs.

In order to achieve the above implementation objectives, the inventor developed the following animal growth identification method, the implementation steps of which include:

A. Shooting images: using at least one photography unit to shoot animals within a preset range of a breeding area, and transmitting the three-dimensional visual images and thermal images of the animals to a control unit;

B. Construct image outline: Then let the control unit construct its stereoscopic visual outline and thermal image outline for one of the animals in the stereoscopic visual image frame and thermal image frame;

C. Obtain the corrected outline: The control unit then superimposes the stereoscopic vision outline and the thermal image outline of the animal to obtain the corrected outline of the animal;

D. Calculate the volume of the animal: continue to use the control unit to measure the edge of the correction contour to obtain the depth and bottom area of the edge of the correction contour, and then calculate the volume of the animal;

E. Obtain the volume-to-weight conversion ratio: The control unit will identify various condition factors of the animal and output the volume-to-weight conversion ratio that meets the condition factors;

F. Calculate the weight of the animal: The control unit then substitutes the obtained volume of the animal into the volume-to-weight conversion ratio to calculate the weight of the animal;

G. Statistics of the total weight of animals: The control unit then calculates the weights of the many animals within the preset range of the breeding area photographed by the photography unit one by one, and then adds up the weights of the many animals. And the weight statistical result is displayed on a display unit.

The animal growth identification method as described above, wherein the animal growth identification method further includes an abnormality warning step, which enables the control unit to compare the thermal image of the animal with the animal's normal body temperature to determine the animal's normal body temperature. Whether the animal is sick or dead, if it is determined that the animal is sick or dead, an abnormal warning message will be displayed on the display module.

The animal growth identification method as described above, wherein the condition factors of the animal identified by the control unit include at least one of the animal's species, growth stage and growth season.

The inventor further developed the following animal growth identification system, which mainly includes a fixed unit, which is installed in a breeding area, and at least one photography unit is installed on the fixed unit, and the photography unit is inside It is equipped with at least two stereoscopic imaging lenses and at least one thermal imaging lens. It also includes a control unit for signal connection with the photography unit, and an animal growth recognition artificial intelligence program is built in the control unit. The animal growth recognition artificial intelligence program The smart program includes a three-dimensional image contour construction module, a thermal image contour construction module, a contour correction module, a volume calculation module, a volume-to-weight conversion ratio module, a weight calculation module and a weight statistics module. The group is operated by the control unit connected to each module of the animal growth recognition artificial intelligence program. Among them, the photography unit shoots the farmed animals within a preset range of the breeding area and combines the captured three-dimensional visual images. and the thermal image frame is transmitted to the control unit, the three-dimensional image contour construction module constructs a three-dimensional visual contour of one of the animals in the stereoscopic vision image frame, and the thermal image contour construction module constructs a three-dimensional visual contour of the animal in the thermal image frame The one animal constructs its thermal image outline, and the outline correction module superimposes the animal's stereoscopic vision outline and the thermal image outline correspondingly to obtain the corrected outline of the one animal, and the volume calculation module is Measure the edge of the correction outline to obtain the base area and depth of the edge of the correction outline, and then calculate the volume of the animal. The volume-to-weight conversion ratio module will identify various condition factors of the animal to output The volume and weight conversion ratio that meets the condition factors, and the weight calculation module will substitute the volume of the animal obtained from the volume calculation module into the volume and weight conversion ratio provided by the volume and weight conversion ratio module to calculate The weight of the animal is obtained, and the weight statistics module adds up statistics of the weight of a number of animals within a preset range captured by the photography unit, and connects the control unit to a display unit to calculate the weight of the animal. The weight statistics results are displayed on the display unit.

As mentioned above, the animal growth identification system, wherein the animal growth identification artificial intelligence program further includes an abnormality warning module, the abnormality warning module will identify the body temperature of the animal in the thermal image screen to match the animal's body temperature. The normal body temperature is compared to determine whether the animal is sick or dead. If it is determined that the animal is sick or dead, the control unit is driven to display an abnormal warning message on the display module.

In the above animal growth identification system, the animal condition factors identified by the volume-to-weight conversion ratio module include at least one of the animal's species, growth stage, and growth season.

In this way, when the present invention is implemented, at least one photography unit takes pictures of animals in a breeding area, and transmits the captured stereoscopic vision images and thermal images to a control unit, so that the control unit can respectively Construct the stereoscopic visual outline and thermal image outline of the farmed animal, and then superimpose the two outlines to obtain the corrected outline of the animal. Then calculate the volume of the corrected outline, and then identify the species, growth stage and other conditions of the animal. The factor is to output the corresponding volume-to-weight conversion ratio, and then the obtained volume is substituted into the volume-to-weight conversion ratio to obtain the weight of the animal. This way, the weight of the many animals photographed in the breeding area can be added up. Statistics can be used to accurately estimate the harvesting time of animals in the breeding area, thereby effectively saving feed costs and other benefits.

In order to have a more complete and clear disclosure of the technical means of the present invention and the effects it can achieve, the details are described as follows. Please refer to the disclosed drawings and drawing numbers:

First of all, please refer to the first and third figures, which are animal growth identification methods and systems of the present invention, which mainly include a fixed unit (1). The fixed unit (1) is a bracket installed above the breeding area. , and at least one photography unit (2) is set on the fixed unit (1). The photography unit (2) is equipped with at least two stereoscopic imaging lenses (21) and at least one thermal imaging lens (22). , and also includes a control unit (3). The control unit (3) can be a desktop computer, notebook computer or tablet computer, etc., to be connected with the photography unit (2), and in the control unit (3) ) has a built-in animal growth recognition artificial intelligence program (4). The animal growth recognition artificial intelligence program (4) includes a three-dimensional image contour construction module (41), a thermal image contour construction module (42), and an outline. Calibration module (43), a volume calculation module (44), a volume-weight conversion ratio module (45), a weight calculation module (46), a weight statistics module (47) and an abnormality warning module (48), so that the control unit (3) is connected to the operation of each module of the animal growth recognition artificial intelligence program (4), and the control unit (3) is connected to a display unit (5) such as a screen.

Accordingly, when the present invention is implemented, please also refer to the second figure. The implementation steps include:

A. Shooting images: The photography unit (2) is installed on the fixed unit (1) and located above a breeding area, and then the photography unit (2) is allowed to shoot a preset range of the breeding area. Chickens, pigs, cows and other farmed animals (6) are stored in the farm, and the three-dimensional visual images and thermal images of the captured animals (6) are transmitted to the control unit (3);

B. Constructing image contours: The three-dimensional image contour construction module (41) established by the animal growth recognition artificial intelligence program (4) built in the control unit (3) uses 3D point cloud technology to construct the stereoscopic visual image. One of the animals (6) constructs its stereoscopic visual outline (61), and the thermal image outline construction module (42) uses 3D point cloud technology to construct its thermal image of the one of the animals (6) in the thermal image. Image outline(62):

C. Obtain the corrected contour: please refer to the fourth figure, and then use the contour correction module (43) to construct the three-dimensional visual contour (61) and thermal image contour (62) of the animal (6) ) corresponding superposition to obtain the corrected outline of the animal (6) after removing feathers or hair;

D. Calculate the animal volume: continue to measure the edge of the correction outline by the volume calculation module (44) to obtain the average depth of the edge of the correction outline, and the depth and bottom of each edge point pixel of the correction outline. area, and then substitute it into The volume solution formula of , where p is the average depth of the edge, di is the depth of the i-th pixel, and Ai is the bottom area of the i-th pixel. Accordingly, it is calculated through the corrected outline of the animal (6) The size of the animal (6);

E. Obtain the volume-to-weight conversion ratio: Then the volume-to-weight conversion ratio module (45) will identify at least one of the condition factors such as the species, growth stage, and growth season of the animal (6) to output an output that matches these conditions. The volume-to-weight conversion ratio of the conditional factors is obtained by calculating the actual weight of general animals that conforms to the species, growth stage, growing season and other conditional factors through the neural network;

F. Calculate the weight of the animal: The weight calculation module (46) then obtains the volume of the animal (6) from the volume calculation module (44) and substitutes it into the volume-to-weight conversion ratio module (45). After calculating the volume-to-weight conversion ratio of the animal (6)'s species, growth stage, growing season and other conditional factors, the weight of the animal (6) can be calculated;

G. Statistics of the total weight of animals: After calculating the weight of many animals (6) within the preset range of the breeding area captured by the photography unit (2) one by one, the weight statistics module (47) The weights of the plurality of animals (6) are summed up to display the weight statistics results on the display unit (5) connected to the control unit (3).

Through this, the breeder can accurately know the group weight distribution status of the many animals (6) in the breeding area, and then accurately estimate the best harvesting time and feed feeding days of the animals (6) in the breeding area, so as to Achieving substantial benefits such as effectively saving feed costs and increasing profits for farmers. It is also worth mentioning that the animal growth identification artificial intelligence program (4) of the present invention is equipped with an abnormality warning module (48), and further includes an abnormality warning step. When the photography unit (2) When the thermal image of 6) is transmitted to the control unit (3), the abnormality warning module (48) will identify the body temperature of the animal (6) in the thermal image to compare it with the normal body temperature of the animal (6). Yes, and to determine whether the animal (6) is sick or dead, if it is determined that the animal (6) is sick or dead, the control unit (3) is driven to display an abnormal warning message on the display unit (5), accordingly , to facilitate breeders to promptly dispose of sick or dead animals and avoid greater losses such as the spread of disease.

The foregoing embodiments or drawings do not limit the implementation of the animal growth identification method and its system of the present invention. Any appropriate changes or modifications made by those with ordinary knowledge in the technical field shall be regarded as not departing from the patent scope of the present invention. .

It can be seen from the above structure and implementation that the present invention has the following advantages:

1. The animal growth identification method and its system of the present invention introduce the technology of visual calculation of the weight of farmed animals, which can monitor a number of farmed animals within a range of the breeding area at one time, thereby accurately obtaining the information of the number of animals in the breeding area. Group weight distribution status, and then predict the best harvest time and feed feeding days of these farmed animals, so as to achieve effective savings in feed costs and other benefits.

2. The animal growth identification method and its system of the present invention take thermal images of animals to identify the body temperature of the animals, and then determine whether the animals are sick or dead, so as to display warning messages when abnormalities occur. Accordingly, to facilitate Dispose of sick or dead animals promptly to avoid greater losses such as the spread of disease.

3. The animal growth identification method and system of the present invention can identify the species, growth stage and season of different animals to obtain the corresponding volume and weight conversion ratio. This can be convenient even if various animals are mixed in the breeding farm. Calculate mixed animals separately to accurately estimate growth and harvest times for each species.

To sum up, the embodiments of the present invention can indeed achieve the expected effects, and the specific structure disclosed has not only not been seen in similar products, but has also not been disclosed before the application. It has fully complied with the provisions of the patent law and If you apply for an invention patent in accordance with the law, please review it and grant a patent, which will be very convenient.

1: Fixed unit

2: Photography unit

21:Stereoscopic imaging lens

22: Thermal imaging lens

3:Control unit

4: Artificial intelligence program for animal growth identification

41: Three-dimensional image contour construction module

42: Thermal image contour construction module

43:Contour correction module

44: Volume calculation module

45: Volume to weight conversion ratio module

46: Weight calculation module

47: Weight statistics module

48: Abnormal warning module

5:Display unit

6: animals

61: Stereoscopic vision outline

62: Thermal image contour

Figure 1: System architecture diagram of the present invention

Second figure: flow chart of the present invention

The third figure: usage status diagram of the present invention

Figure 4: Overlay state diagram of stereoscopic vision contour and thermal image contour of the present invention

2: Photography unit

21:Stereoscopic imaging lens

22: Thermal imaging lens

3:Control unit

4: Artificial intelligence program for animal growth identification

41: Three-dimensional image contour construction module

42: Thermal image contour construction module

43:Contour correction module

44: Volume calculation module

45: Volume to weight conversion ratio module

46: Weight calculation module

47: Weight statistics module

48: Abnormal warning module

5:Display unit

Claims (6)

An animal growth identification method, the implementation steps of which include: A. Shooting images: using at least one photography unit to shoot animals within a preset range of a breeding area, and transmitting the three-dimensional visual images and thermal images of the animals to a control unit; B. Construct image outline: Then let the control unit construct its stereoscopic visual outline and thermal image outline for one of the animals in the stereoscopic visual image frame and thermal image frame; C. Obtain the corrected outline: The control unit then superimposes the stereoscopic vision outline and the thermal image outline of the animal to obtain the corrected outline of the animal; D. Calculate the volume of the animal: continue to use the control unit to measure the edge of the correction contour to obtain the depth and bottom area of the edge of the correction contour, and then calculate the volume of the animal; E. Obtain the volume-to-weight conversion ratio: The control unit will identify various condition factors of the animal and output the volume-to-weight conversion ratio that meets the condition factors; F. Calculate the weight of the animal: The control unit then substitutes the obtained volume of the animal into the volume-to-weight conversion ratio to calculate the weight of the animal; G. Statistics of the total weight of animals: The control unit then calculates the weights of the many animals within the preset range of the breeding area photographed by the photography unit one by one, and then adds up the weights of the many animals. And the weight statistical result is displayed on a display unit. The animal growth identification method as described in claim 1, wherein the animal growth identification method further includes an abnormality warning step, which enables the control unit to compare the thermal image of the animal with the animal's normal body temperature to determine Determine whether the animal is sick or dead. If it is judged that the animal is sick or dead, an abnormal warning message is displayed on the display module. The animal growth identification method as described in claim 1, wherein the condition factors of the animal identified by the control unit include at least one of the animal's species, growth stage and growth season. An animal growth identification system mainly includes a fixed unit, which is installed in a breeding area, and at least one photography unit is set on the fixed unit, and the photography unit is equipped with at least two three-dimensional images The lens and at least one thermal imaging lens also include a control unit for signal connection with the photography unit, and an animal growth recognition artificial intelligence program is built into the control unit, and the animal growth recognition artificial intelligence program includes a three-dimensional image A contour construction module, a thermal image contour construction module, a contour correction module, a volume calculation module, a volume-to-weight conversion ratio module, a weight calculation module and a weight statistics module are provided by the control unit Linking the operation of each module of the animal growth identification artificial intelligence program, the photography unit captures the farmed animals within a preset range of the breeding area, and transmits the captured stereoscopic vision images and thermal images to the The control unit, the three-dimensional image contour construction module constructs the three-dimensional visual contour of one of the animals in the three-dimensional visual image frame, and the thermal image contour construction module constructs the one of the animal in the thermal image frame. Thermal image contour, and the contour correction module superimposes the stereoscopic vision contour and the thermal image contour of the animal to obtain the corrected contour of one of the animals, and the volume calculation module measures the edge of the corrected contour , to obtain the base area and depth of the corrected outline edge, and then calculate the volume of the animal. The volume-to-weight conversion ratio module will identify various conditional factors of the animal to output the volumetric weight that meets the conditional factors. Conversion ratio, and the weight calculation module substitutes the volume of the animal obtained from the volume calculation module into the volume-to-weight conversion ratio provided by the volume-to-weight conversion ratio module to calculate the weight of the animal, and The weight statistics module sums up the weights of a number of animals within a preset range captured by the photography unit, and connects the control unit to a display unit to display the weight statistics results on the display. on the unit. The animal growth identification system as described in claim 4, wherein the animal growth identification artificial intelligence program further includes an abnormality warning module, and the abnormality warning module will identify the body temperature of the animal in the thermal image frame to communicate with the animal growth identification system. The normal body temperature of the animal is compared to determine whether the animal is sick or dead. If it is determined that the animal is sick or dead, the control unit is driven to display an abnormal warning message on the display module. The animal growth identification system as described in claim 4, wherein the animal condition factors identified by the volume-to-weight conversion ratio module include at least one of the animal's species, growth stage, and growth season.

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