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| Logs End Detection and Statistics by Color Difference Clustering |
| TANG Hao1,WANG Ke-jian1,LI Xiao-ye1,JIAN Wen-hao2,GU Jian-cai3 |
1. College of Information Science and Technology, Agriculture University of Hebei, Baoding, Hebei 071000, China
2. Mulan Weichang State-owned Forest Farm Administration of Hebei Province, Chengde, Hebei 067000, China
3. College of Forestry, Agriculture University of Hebei, Baoding, Hebei 071000, China |
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Abstract Logs end detection is disturbed by the natural environment. An end detection method for logs accumulation state in natural environment is introduced based on image processing technology. Segmentation of logs images into logs sections, pores and backgrounds by color difference clustering to remove background interference and extracting logs end, segmentation counting is performed using hierarchical opening operation and an improved watershed algorithm. The results show that the correct detection rate is 91.88%, the false detection rate is 5.08%, and the missed detection rate is 8.12% under the high interference environment of natural environment. The method satisfies the requirement for the identification and counting of logs.
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Received: 16 April 2019
Published: 08 June 2020
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2020, Vol. 41 
