Automatic detection of ruminant cows’ mouth area during rumination based on machine vision and video analysis technology

Authors

  • Yanru Mao 1. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China; 2. Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Yangling, Shaanxi 712100, China; 3. Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling, Shaanxi 712100, China
  • Dongjian He 1. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China; 2. Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Yangling, Shaanxi 712100, China; 3. Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling, Shaanxi 712100, China
  • Huaibo Song 1. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China; 2. Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture, Yangling, Shaanxi 712100, China; 3. Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling, Shaanxi 712100, China

Keywords:

ruminant cows, mouth area, automatic detection, machine vision, video analysis technology, ruminant behavior, optical flow

Abstract

In order to realize the automatic monitoring of ruminant activities of cows, an automatic detection method for the mouth area of ruminant cows based on machine vision technology was studied. Optical flow was used to calculate the relative motion speed of each pixel in the video frame images. The candidate mouth region with large motion ranges was extracted, and a series of processing methods, such as grayscale processing, threshold segmentation, pixel point expansion and adjacent region merging, were carried out to extract the real area of cows’ mouth. To verify the accuracy of the proposed method, six videos with a total length of 96 min were selected for this research. The results showed that the highest accuracy was 87.80%, the average accuracy was 76.46% and the average running time of the algorithm was 6.39 s. All the results showed that this method can be used to detect the mouth area automatically, which lays the foundation for automatic monitoring of cows’ ruminant behavior. Keywords: ruminant cows, mouth area, automatic detection, machine vision, video analysis technology, ruminant behavior, optical flow DOI: 10.25165/j.ijabe.20191201.4268 Citation: Mao Y R, He D J, Song H B. Automatic detection of ruminant cows’ mouth area during rumination based on machine vision and video analysis technology. Int J Agric & Biol Eng, 2019; 12(1): 186–191.

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Published

2019-02-01

How to Cite

(1)
Mao, Y.; He, D.; Song, H. Automatic Detection of Ruminant cows’ Mouth Area During Rumination Based on Machine Vision and Video Analysis Technology. Int J Agric & Biol Eng 2019, 12, 186-191.

Issue

Vol. 12 No. 1 (2019): IJABE

Section

Information Technology, Sensors and Control Systems

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