Sows parturition detection method based on machine vision

被引：0
|
作者：
Liu, Longshen [1 ]
Shen, Mingxia [1 ]
Bo, Guangyu [1 ]
Zhou, Bo [2 ]
Lu, Mingzhou [1 ]
Yang, Xiaojing [3 ]
机构：
[1] College of Engineering, Nanjing Agricultural University
[2] College of Animal Science and Technology, Nanjing Agricultural University
[3] Key Lab. of Animal Physiology and Biochemistry, Ministry of Agriculture, Nanjing Agricultural University
来源：
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | 2014年 / 45卷 / 03期
关键词：
Machine vision; Matching by semi-circle; Moving objects detection; Sows parturition;
D O I：
10.6041/j.issn.1000-1298.2014.03.039
中图分类号：
学科分类号：
摘要：
Automation and industrialization is the trend of pig industry. Real-time detection of parturition is one of the key technologies of sow automation farming. Video image features of sows parturition were analyzed to detect sows parturition by recognizing piglet. The moving objects were detected based on the improved single Gaussian model. Disturbance of sow moving was removed by the arithmetic of matching semi-circle. According to the color and size characteristics of newborn piglets, targets were recognized. Test results showed that the sow object could be recognized effectively by the proposed approach. The moving objects detection method based on the improved single Gaussian model detected the slow-moving piglet completely after eliminate interference.
引用
收藏
页码：237 / 242
页数：5
相关论文
共 17 条
  • [1] Liu L., Shen M., Yao W., Et al., Acquisition and analysis of sows' behavior before farrowing based on acceleration sensor, Transactions of the Chinese Society for Agricultural Machinery, 44, 3, pp. 192-196, (2013)
  • [2] Labrecque S., Labrecque R., Labrecque G., Birth monitoring system for piglets: US, 20080266115 A1, (2008)
  • [3] (2011)
  • [4] (2011)
  • [5] Shao B., Xin H., A real-time computer vision assessment and control of thermal comfort for group-housed pigs, Computers and Electronics in Agriculture, 62, 2, pp. 15-21, (2008)
  • [6] Ahrendt P., Gregersen T., Karstoft H., Development of a real-time computer vision system for tracking loose-housed pigs, Computers and Electronics in Agriculture, 76, 2, pp. 169-174, (2011)
  • [7] Zhu W., Pu X., Li X., Et al., Automatic identification system of pigs with suspected case based on behavior monitoring, Transactions of the CSAE, 26, 1, pp. 188-192, (2010)
  • [8] Zhu W., Ji B., Qin F., Detection of foreground-frame of pig using edge model based on pseudosphere-operator, Transactions of the CSAE, 28, 12, pp. 189-194, (2012)
  • [9] Yang Y., Teng G., Li B., Et al., Measurement of pig weight based on computer vision, Transactions of the CSAE, 22, 2, pp. 127-131, (2006)
  • [10] He L., Research and implementation on swine body identification based on the characteristic of image texture and color, (2010)
12