农业机械学报2017，Vol.48Issue(4)：173-179,7.DOI:10.6041/j.issn.1000-1298.2017.04.023
基于机器学习的奶牛深度图像身体区域精细分割方法
Fine Segment Method of Cows' Body Parts in Depth Images Based on Machine Learning
摘要
Abstract
The recognition of cows' body parts is essential for providing accurate details of the cows' shape,which is the fundamental prerequisite for locomotion scoring,posture detection and behavioral quantifications.The objective was to develop a robust depth feature in order to reduce the difficulty in building the classifier and detect cows' body parts with higher accuracy.Therefore,a method for segmenting cows' body parts was proposed,including the head,neck,body,forelimbs,hind limbs and tail,with high accuracy on the basis of depth image processing and machine learning.The local binary patterns of each pixel under several sampling radii were used as the features with which the filtering rules were designed,and a decision forest was trained and tested to classify the pixels into six groups.Furthermore,totally 288 depth images were captured from 30 cows;150 images were randomly selected to build three decision trees,and the rest images were used for testing.The results showed that when the number of sampling radii and training layers were 30 and 20,respectively,the recognition rate reached 95.15％.Among the cows' body parts,the recognition rate of tail was 54.97％,and the minimum recognition rate of other parts was 89.22％.In some cases that tail was too close to trunk to segment tail from trunk by human marker,the decision trees recognized the tail successfully.The average recognition time for pixel were 0.38 ms and 0.25 ms,and the recognition time for cow target were 20.30 s and 15.25 s for the conventional method and new method,respectively.This LBP-based depth image feature was translation-invariant and rotation-invariant and had fewer parameters.The results showed that the new method proposed was more effective in recognizing small and complex structures of the cow target with higher accuracy.Compared with the typical depth image features,the new feature employed was capable of extracting the details of cows' body and recognizing complex parts more accurately with fewer parameters and simple model.关键词
奶牛/目标检测/肢干分割/深度图像/机器学习Key words
cows/target detection/body segment/depth image/machine learning分类
农业科技引用本文复制引用
赵凯旋,李国强,何东健..基于机器学习的奶牛深度图像身体区域精细分割方法[J].农业机械学报,2017,48(4):173-179,7.基金项目
国家自然科学基金项目(61473235) （61473235）
