کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6540012 | 1421106 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Automatic individual identification of Holstein dairy cows using tailhead images
ترجمه فارسی عنوان
شناسایی خودکار فردی از گاوهای شیری هلشتاین با استفاده از تصاویر دمدمی مزاج
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
The implementation of dairy cow identification will be of great significance in precision animal management based on computer vision. In this study, a computer vision technique to identify the individual dairy cows automatically was proposed and evaluated. The tailhead image, which was used as a Region of Interest (ROI), was captured in a dairy farm. Zernike moments were used as descriptors of shape characteristics for the white pattern on the ROI. Two groups of Zernike moments were extracted from the preprocessed image and classified using four alternative classifiers, namely, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), artificial neural network (ANN) and support vector machines (SVM). The QDA classifier had the highest value, 99.7%, while the SVM classifier had the highest precision, 99.6%. Comprehensively, the QDA and SVM classifiers presented the best performance, with equal F1 score of 0.995. These results show that the low-order Zernike moment feature, along with the QDA and SVM algorithms is an effective approach for individual dairy cow identification and has significant applications in precision animal management.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 142, Part B, November 2017, Pages 622-631
Journal: Computers and Electronics in Agriculture - Volume 142, Part B, November 2017, Pages 622-631
نویسندگان
Wenyong Li, Zengtao Ji, Lin Wang, Chuanheng Sun, Xinting Yang,