基于圆形约束CV-LIF模型的原木端面图像分割-计算机工程与应用.PDFVIP

Computer Engineering and Applications 计算机工程与应用 2014 ，50（18） 147 基于圆形约束CV-LIF 模型的原木端面图像分割 1 1，2 1 官 俊 ，任洪娥 ，宋 爽 1 1，2 1 GUAN Jun ，REN Hong ’e ，SONG Shuang 1.东北林业大学 信息与计算机工程学院，哈尔滨 150040 2.黑龙江省林业智能装备工程研究中心，哈尔滨 150040 1.College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, China 2.Forestry Intelligent Equipment Engineering Research Center, Harbin 150040, China GUAN Jun, REN Hong ’e, SONG Shuang. Log end image segmentation based on circle dependent CV-LIF model. Computer Engineering and Applications, 2014, 50 （18）：147-151. Abstract ：The paper, in allusion to the segmentation problems of log end image obtained in natural conditions, and accord- ing to the characteristics of the log end image, improves the traditional CV （Chan and Vese ）model, and fits the interior of evolving contour with gradient information. At the same time, with reference to the Local Image Fitting （LIF ）model, and joining with circle prior knowledge, it proposes an improved active contour model based on circle dependent, which is called CV-LIF. The model combines global and local energy together to restrain the evolution of contours. On the basis of pre-segmentation image, it represents the regions which are to be segmented with multi-level set, and does re-segmentation to each level set region with the model proposed. This model solves the problem of inaccuracy of multiple logs ends image segmentation under the complex background. Experiments for single log end and multiple logs ends segmentation indicate that the model can segment the logs ends correctly, and has better anti-noise performance. It can effectively overcome the interference of background, and runs faster. Key words ：log end; level set; Chan and Vese（CV ）model; Local Image Fitting （LIF ）model; circle dependent 摘 要：针对自然条件下原木端面图像的分割问题，结合原木