TY - GEN
T1 - Cattle AutoID
T2 - 8th International Conference on Sustainable Information Engineering and Technology, SIET 2023
AU - Kusakunniran, Worapan
AU - Phongluelert, Kunthorn
AU - Sirisangpaival, Chanathip
AU - Narayan, Osh
AU - Thongkanchorn, Kittikhun
AU - Wiratsudakul, Anuwat
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/10/24
Y1 - 2023/10/24
N2 - Existing solutions of animal identification (i.e., cattle in this research project) are based on RFID, ear tag, and microchip. However, they are facing with difficulties of high cost, dislodged and lost, and harm to human operators and animals. Therefore, this paper proposes a biometric based solution of cattle identification using cattle's face images. The proposed method is developed using a convolutional neural network (CNN) for both main steps of face localization and face recognition. The face localization model is trained using a Single-Shot Detector (SSD) architecture, where the face recognition model is trained based on FaceNet. The proposed method is validated using our dataset containing 2,432 cattle images from 152 different cattle. It achieves 94.74% and 83.45% for subject-based and image-based accuracies respectively.
AB - Existing solutions of animal identification (i.e., cattle in this research project) are based on RFID, ear tag, and microchip. However, they are facing with difficulties of high cost, dislodged and lost, and harm to human operators and animals. Therefore, this paper proposes a biometric based solution of cattle identification using cattle's face images. The proposed method is developed using a convolutional neural network (CNN) for both main steps of face localization and face recognition. The face localization model is trained using a Single-Shot Detector (SSD) architecture, where the face recognition model is trained based on FaceNet. The proposed method is validated using our dataset containing 2,432 cattle images from 152 different cattle. It achieves 94.74% and 83.45% for subject-based and image-based accuracies respectively.
KW - Animal Biometric
KW - Cattle Reidentification
KW - Deep Learning
KW - Face Recognition
UR - http://www.scopus.com/inward/record.url?scp=85182398335&partnerID=8YFLogxK
U2 - 10.1145/3626641.3627215
DO - 10.1145/3626641.3627215
M3 - Conference contribution
AN - SCOPUS:85182398335
T3 - ACM International Conference Proceeding Series
SP - 570
EP - 574
BT - SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology
PB - Association for Computing Machinery
Y2 - 24 October 2023 through 25 October 2023
ER -