Tire Impressions Image Segmentation Algorithm Based on C-V Model without Re-initialization
In this paper．we present a new tire impressions jmage segmentation algorithm based on C-V model without re—initialization by introducing an internal energy term that penalizes the deviation of the Ievel set funotion from a signed distance function into the C-V model．The proposed model Can keep the approximately the IeveI set funotion as a signed distance function during the CUrve evolution．The level set function can be inifialized with general functions that are more efficient to construct and easier to use than the widely used signed distance function in practice and speed up the curve evolution．Therefore,the consuming time to compute a signed distance function from an initiaI eurve jn irregular shape is saved．The proposed algorithm has been applied to both printing and collected tire impressions images in the scene with promising results．
tire impressions C-V model Level set Signed distance function image segmentation
Wang Zhen Wang Yunpeng Li Shiwu
College of Traffic, Jilin University Changchun, China China Criminal Police University Shenyang, Chi College of Traffic, Beihang university Beijing, China College of Traffic, Jilin University Changchun, China
国际会议
西安
英文
541-545
2011-05-13（万方平台首次上网日期，不代表论文的发表时间）