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Validation of Biometric Identification of Dairy Cows based on Udder NIR Images

机译:基于乳房近红外光谱图像的奶牛生物特征识别验证

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Identifying dairy cows with infections such as mastitis or cows on medications is an extremely important task and legally required by the FDA's Pasteurized Milk Ordinance. The milk produced by these dairy cows cannot be allowed to mix with the milk from healthy cows or it risks contaminating the entire bulk tank or milk truck. Ear tags, ankle bands, RFID tags and even iris patterns are some of the identification methods currently used in the dairy farms. In this work we propose the use of NIR images of cow's mammary glands as a novel biometric identification modality. Two datasets, containing 302 samples from 151 cows has been collected and various machine learning techniques applied to demonstrate the viability of the proposed biometric modality. The results suggest promising identification accuracy for samples collected over consecutive days.
机译:识别感染如乳腺炎或奶牛感染的奶牛是一项非常重要的任务,并且是FDA的《巴氏杀菌牛奶条例》的法律要求。这些奶牛生产的牛奶不能与健康奶牛的牛奶混合,否则有污染整个散装储罐或牛奶车的风险。耳标,脚腕带,RFID标签甚至虹膜图案是目前奶牛场中使用的一些识别方法。在这项工作中,我们建议使用牛乳腺的NIR图像作为一种新颖的生物识别方式。已经收集了两个数据集,其中包含来自151头母牛的302个样本,并且应用了各种机器学习技术来证明所提出的生物特征识别方法的可行性。结果表明,连续几天收集的样品具有良好的鉴定准确性。

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