Identification of Japanese Black Cattle by the Faces for Precision Livestock Farming
학회지: 바이오시스템공학 29(4), 341 - 346 쪽
저자: 김현태, 池田善郞, 西律貴久, 이인복
개요
Recent livestock people concern not only increase of production, but also superior quality of animal -breeding environment. So far, the optimization of the breeding and air environment has been focused on the production increase. In the very near future, the optimization will be emphasized on the environment for the animal welfare and health. Especially, cattle farming demands the precision livestock farming and special attention has to be given to the management of feeding, animal health and fertility.
The management of individual animal is the first step for precision livestock farming and animal welfare, and recognizing each individual is imporant for that. Though electronic identification of a cattle such as RFID(Radio Frequency Identification) has many advantages, RFID implementations practically involve several problems such as the reading speed and distance. ln that sense, computer vision might be more effective than RFID for the identification of an individual animal.
The researches on the identification of cattle via image processing were mostly performed with the cows having black-white pattems of the Holstein. But, the native Korean and Japanese cattle do not have any definite pattem on the body. The purpose of this research is to identify the Japanese black cattle that does not have a body pattem using computer vision technology and neural network algorithm.
Twelve heads of Japanese black cattle have been tested to veri the proposed scheme. The values of input parameter were specified and then computed using the face images of cattle. The images of cattle faces were trained using associate neural network algorithm, and the algorithm was verified by the face images that were transformed using brightness， distortion, and noisε factors.
As a result， there was difference due to transform ratio of the brightness, distortion, and noisε. And, the proposed algorithm could identify 100% in the range from - 3 to + 3 degrees of the brightness, from - 2 to + 4 degrees of the distortion, and from 0% to 60% of the noise transformed images. It is concludεd that our system can not bε applied in real time recognition of the moving cows, but can be used for the cattle being at a standstill.
Download Link :
https://www.researchgate.net/profile/I-B_Lee/publication/289530738_Bioprocess_Engineering_Identification_of_Japanese_Black_Cattle_by_the_Faces_for_
Precision_Livestock_Farming/links/568f3c4908aead3f42f08623/Bioprocess-Engineering-Identification-of-Japanese-Black-Cattle-by-the-Faces-for-Precision-Livestock-Farming.pdf
http://www.koreascience.or.kr/article/ArticleFullRecord.jsp?cn=NOGGB5_2004_v29n4_341