CAJ | 학술논문

Otsu自适应阈值法是一种经典的图像阈值分割方法，在其基础上发展起来的2维Otsu法及其改进算法由于存在计算(或空间)复杂度较高、抗噪能力差、难以扩展到多阈值等不足而制约了其应用。该文针对2维Otsu法的不足，将噪声点的出现视为小概率事件，用噪声点的邻域均值代替其灰度值，将噪声点转换为目标(或背景)像素，减少了图像中的噪声点数量；继而直接采用1维Otsu法进行分割，以较小的代价获得良好的分割效果。算法分析及测试实验表明：与现有2维Otsu法相比，该算法在复杂度、抗噪性、多阈值扩展性等方面都有明显改善。
Otsu자괄응역치법시일충경전적도상역치분할방법，재기기출상발전기래적2유Otsu법급기개진산법유우존재계산(혹공간)복잡도교고、항조능력차、난이확전도다역치등불족이제약료기응용。해문침대2유Otsu법적불족，장조성점적출현시위소개솔사건，용조성점적린역균치대체기회도치，장조성점전환위목표(혹배경)상소，감소료도상중적조성점수량；계이직접채용1유Otsu법진행분할，이교소적대개획득량호적분할효과。산법분석급측시실험표명：여현유2유Otsu법상비，해산법재복잡도、항조성、다역치확전성등방면도유명현개선。
Otsu adaptive threshold algorithm is a classic image segmentation method. The two-dimensional Otsu algorithm and its improvements which based on original Otsu algorithm are restricted, due to their computation(or space) complexity, inability for anti-noise, difficulty to extend to multilevel thresholding. In order to improve these shortages, regarding noise points’ appearances as small probability events, noise point is changed to objective(or background) pixel by using its neighborhood average gray level to instead its gray level. Then the processed image is segmented through one-dimensional Otsu. So this method obtain good performance at low cost. The experimental result shows that this method has significant improvements in complexity, ability for anti-noise, ability for extending to multilevel thresholding and so on.