Automatic Detection of Cow's Oestrus in Audio Surveillance System

被引:49
作者
Chung, Y. [1 ]
Lee, J. [1 ]
Oh, S. [1 ]
Park, D. [1 ]
Chang, H. H. [2 ]
Kim, S. [3 ]
机构
[1] Korea Univ, Coll Sci & Technol, Dept Comp & Informat Sci, Sejong 339700, South Korea
[2] Gyeongsang Natl Univ, Coll Agr & Life Sci, Inst Agr & Life Sci, Dept Anim Sci, Jinju 660701, South Korea
[3] Gyeongsang Natl Univ, Coll Vet Med, Jinju 660701, South Korea
来源
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES | 2013年 / 26卷 / 07期
关键词
Cow's Oestrus Detection; Sound Data; Mel Frequency Cepstrum Coefficient; Feature Subset Selection; Support Vector Data Description; DAIRY-COWS; CATTLE; TIME; AGRICULTURE; RECOGNITION; PEDOMETER; FOOD;
D O I
10.5713/ajas.2012.12628
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced for the detection of oestrus, a more accurate and practical method is still required. In this paper, we propose an efficient data mining solution for the detection of oestrus, using the sound data of Korean native cows (Bos taurus coreanea). In this method, we extracted the mel frequency cepstrum coefficients from sound data with a feature dimension reduction, and use the support vector data description as an early anomaly detector. Our experimental results show that this method can be used to detect oestrus both economically (even a cheap microphone) and accurately (over 94% accuracy), either as a standalone solution or to complement known methods.
引用
收藏
页码:1030 / 1037
页数:8
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