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
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.
[1]才琪, 陈绍志, 赵荣. 中央林业投资与林业经济增长的互动关系 [J]. 林业科学, 2015, 51(9): 126-133.
Cai Q, Chen SZ, Zhao R, Interaction relationship between central forestry investment and forestry economic growth in China [J]. Scientia Silvae Sinicae, 2015, 51(9): 126-133.
[2]刁钢. 中国木材供给及政策研究[D]. 北京: 北京林业大学, 2014.
[3]Parker J R. 图像处理与计算机视觉算法及应用(第2版)[M]. 景丽, 译. 北京: 清华大学出版社, 2012: 10-15.
[4]张万红, 朱元骏. 成熟期苹果计数方法研究——以黄土高原样本为例证 [J]. 西南大学学报(自然科学版), 2018, 40(1): 27-34.
Zhang W H, Zhu Y J, A Study on the Method of Counting Number of Ripe Apple Fruits Based on the Sample Obtained from Chinese Loess Plateau [J]. Journal of Southwest University(Natural Science Edition), 2018, 40(1): 27-34.
[5]刘峻, 孙美艳, 焦中元,等. 基于全局阈值迭代的苹果图像分割计数方法 [J]. 安徽农业科学, 2018, 46(29): 180-182,186.
Liu J, Sun M Y, Jiao Z Y, et al. Counting Method of Global Threshold Iterative Algorithm for Apple Images Based on Global Threshold Iterative [J]. Journal of Anhui AgriculturalSciences, 2018, 46(29): 180-182, 186.
[6]Gong A, Yu J, He Y, et al. Citrus yield estimation based on images processed by an Android mobile phone [J]. Biosystems Engineering, 2013, 115(2): 162-170.
[7]Payne A B, Walsh K B, Subedi P P, et al. Estimation of mango crop yield using image analysis Segmentation method [J]. Computers and Electronics in Agriculture, 2013, 91: 57-64.
[8]耿喆,祝海江,杨平,等. 超声C扫描设备定量评价方法研究[J]. 计量学报, 2019, 40(5): 893-899.
Geng Z, Zhu H J, Yang P, et al, Study on Quantitative Evaluation Method of Ultrasonic C-scan Equipment[J]. Acta Metrologica Sinica, 2019, 40(5): 893-899.
[9]曹萌. 管材自动计数系统的研究与应用[D]. 沈阳: 东北大学, 2012.
[10]李中锐. 基于图像处理的棒材识别计数系统设计与实现[D]. 郑州: 郑州大学, 2017.
[11]李良. 基于图像处理的石油套管计数系统研究[D]. 太原: 太原理工大学, 2017.
[12]刘炳乐. 基于机器视觉的成捆棒材计数方法的研究与应用[D]. 天津: 天津工业大学, 2016.
[13]黄松. 基于图像识别方法体细胞计数系统的研究[D]. 太原: 山西农业大学, 2013.
[14]王鑫, 胡洋洋, 杨慧中. 基于迭代腐蚀的粘连细胞图像分割研究 [J]. 南京理工大学学报, 2016, 40(3): 285-289.
Wang X, Hu Y Y, Yang H Z, Segmentation of adherent cell image based on iterative erosion [J]. Journal of Nanjing University of Science and Technology, 2016, 40(3): 285-289.
[15]倪豪, 郑慧峰, 王月兵,等. 基于自动种子区域生长的超声B图像缺陷分割方法 [J]. 计量学报, 2018, 39(6): 878-883.
Ni H, Zheng H F, Wang Y B, et al, Ultrasonic B Image Defect Segmentation Method Based on Automatic Seeded Region Growing[J]. Acta Metrologica Sinica, 2018, 39(6): 878-883.
[16]程淑红, 高许, 周斌. 基于多特征提取和SVM参数优化的车型识别 [J]. 计量学报, 2018, 39(3): 348-352.
Cheng S H, Gao X, Zhou B. Vehicle Recognition Based on Multi-feature Extraction and SVM Parameter Optimization [J]. Acta Metrologica Sinica, 2018, 39(3): 348-352.
[17]钟新秀, 景林, 林耀海. 基于Lab颜色空间阈值分割的原木端面区域识别 [J]. 龙岩学院学报, 2017, 35(2): 95-99.
Zhong X X, Jing L, Lin Y H, Log-end Area Recognition Based on Lab Color Space and Threshold Segmentation [J]. Journal of Longyan University, 2017,35(2): 95-99.
[18]梅振荣, 任洪娥, 朱朦. 基于非线性最小二乘原理的原木端面识别算法 [J]. 计算机工程与应用, 2012, 48(2): 177-178+210.
Mei Z R, Ren H E, Zhu M. Algorithm of log end recognition based on non-linear least squares principle [J]. Computer Engineering andApplications, 2012, 48(2): 177-178, 210.
[19]景林, 林耀海, 黄习培. 基于多特征的成捆原木端面轮廓识别方法 [J]. 计量学报, 2015, 36(4): 370-374.
Jing L, Lin Y H, Huang X P, Outline Extraction of Bundled Logs Cross Section Based on Muliti-feature [J]. Acta Metrologica Sinica, 2015, 36(4): 370-374.
[20]陈广华, 张强, 陈梅倩, 等. 双目视觉的原木径级快速检测算法 [J]. 北京交通大学学报, 2018, 42(2): 22-30.
Chen G H, Zhang Q, Chen M Q, et al. Rapid detection algorithms for log diameter classes based on binocular vision [J]. Journal of Beijing Jiaotong University, 2018, 42(2): 22-30.