LIN Qizhao,WANG Yunlong,HE Xin,et al.Computation method of softwood’s growth ring based on the interactive model and image processing[J].Journal of Forestry Engineering,2019,4(05):121-128.[doi:10.13360/j.issn.2096-1359.2019.05.017]





Computation method of softwood’s growth ring based on the interactive model and image processing
西南林业大学材料科学与工程学院,昆明 650224
LIN Qizhao WANG Yunlong HE Xin QIN Lei QIU Jian*
Material Science and Engineering College, Southwest Forestry University, Kunming 650224, China
针叶材 生长轮 人机交互模式 图像处理 测算方法
softwood growth ring human-computer interaction model image processing computation method
为了快速测算针叶材生长轮,本研究提出基于人机交互模式和图像处理的方法测算针叶材生长轮数。该方法需截取宏观横截面局部矩形图像,经过平滑、直方图均衡化、边缘检测、腐蚀,以及判断连通性后去噪、膨胀等算法处理后,基于稳定状态多数投票计数法,结合人工交互判断得到生长轮数。与传统图像技术处理针叶材生长轮相比,交互模式允许用户在具体测算过程中给定不同阈值,解决了针叶材生长轮测算方法无法适应不同树种、不同样本、不同图像质量的难题; 把边缘检测结果矩形图像左右两侧的颜色处理成与轮界线一致,并使两侧区域与轮界区域构成连通的区域,再通过连通性判断,把其他噪声基本消除,从而达到非常好的去噪效果。基于该方法开发的“针叶材宏观生长轮测算系统”,对生长轮数分别为19,21,104,235的五针白皮松(Pinus squamaia)、杉木(Cunninghamia lanceolata)、翠柏(Calocedrus formosana)、北美红杉(Sequoia sempervirens)进行了处理。试验结果表明,基于交互模式和图像处理的针叶材生长轮测算方法所得出的生长轮数与人工计数的生长轮数相对误差不超过5%。
In dendrochronology, tree growth rings are often calculated.In order to quickly count growth rings of softwood, the computation method based on human-computer interactive model and image processing was used to measure the softwood’s growth rings for four tree species.The local rectangle image of the macro-cross-section was intercepted and processed by smoothing, histogram equalization, edge detection, corrosion, denoising after judging connectivity, expansion and other algorithms.Based on the stable state majority voting counting method, combined with human judgment, the number of growth rings could be obtained.Compared with the traditional image processing technology for counting growth rings of softwood, the interactive model allowed users to give different thresholds in the specific calculation process, which solved the problem that the traditional softwood’s growth rings computation method can not adapt to different tree species, different samples and different image qualities.The colors on the left and right sides of the rectangular image of the boundary detection result were processed as the growth rings boundary line, and the two sides of the image connected with the wheel boundary area.Then using the connectivity judgment, other noises were eliminated to achieve a very good denoising result.Based on this method, a macro-growth-ring measuring system for softwood was developed.Pinus squamaia, Cunninghamia lanceolata, Calocedrus formosana and Sequoia sempervirens with the growth-ring numbers of 19, 21, 104 and 235 were utilized as four representative samples.The first two samples had slight color difference.The growth rings of Pinus squamaia was basically round, and most of the growth rings of Cunninghamia lanceolata were not round.The number of growth rings of the latter two samples was more than 100, and the color difference of Calocedrus formosana was not obvious, while that of Sequoia sempervirens was obvious and the growth rings were dense.The results showed that the relative errors between the numbers of softwood’s growth rings measured based on the interactive model and image processing were no more than 5%.The calculation method proposed in this study needed the user to segment the image manually or to adjust the edge detection image of the growth ring before proceeding with subsequent processing, which was the drawback of this method and needed to be improved in the future work.


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收稿日期:2018-12-13 修回日期:2019-01-23
基金项目:“十三五”国家重点研发计划(2016YFD0600702); 云南省教育厅科学研究基金项目(2019J0191)。
更新日期/Last Update: 2019-09-10