视觉显著区域和主动轮廓结合的图像分割算法  

Image Segmentation Algorithm Combining Visual Salient Regions and Active Contour

作　　者：何亚茹 葛洪伟 HE Yaru;GE Hongwei(Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence,Jiangnan Univer sity,Wuxi,Jiangsu 214122,China;School of Artificial Intelligence and Computer Science,Jiangnan University,Wuxi,Jiangsu 214122,China)

机构地区：[1]江南大学江苏省模式识别与计算机智能工程实验室,江苏无锡214122 [2]江南大学人工智能与计算机学院,江苏无锡214122

出　　处：《计算机科学与探索》2022年第5期1155-1168,共14页Journal of Frontiers of Computer Science and Technology

基　　金：江苏省研究生创新计划项目(KYLX16_0781);江苏高校优势学科建设工程资助项目。

摘　　要：传统区域主动轮廓模型在分割弱边缘图像时,演化曲线受背景干扰,易陷入局部极值导致演化速度缓慢;且由于局部项仅考虑空间信息,无法更好保留目标边界,影响分割精度。针对上述问题,首先利用改进的显著性检测方法,对待分割图像进行预处理操作,获取目标候选区域,自动设置初始化轮廓曲线,并将获取的目标先验信息与待分割图像中具有最大对比度的位图相结合,设计自适应符号函数,对优化LoG能量项进行加权,以线性方式融合到RSF模型中,增强模型自适应能力;其次设计新的局部灰度测度,与局部核函数相结合,改进局部能量项,提高模型在弱边缘处的敏感程度,准确定位目标边界。实验结果表明,该模型能够自动设置初始化轮廓,并有效保留目标边缘细节,视觉及定量实验结果证明了该模型优于目前一些主流的主动轮廓模型。When the traditional regional active contour model is used to segment the weak edge image,the evolu-tion curve is subject to background interference,and it is easy to fall into the local extreme value,which leads to slow evolution speed.Moreover,as the local term only considers the spatial information,it cannot better retain the target boundary,which affects the segmentation accuracy.To solve the above problems,firstly,this paper uses the improved saliency detection algorithm to preprocess the original image,obtains the target candidate regions and auto-matically sets the initial contour curve.In addition,the obtained priori information of the target is combined with the bitmap with the maximum contrast in the image to be segmented.An adaptive symbolic function is designed to weight the optimized LoG(Laplacian of Gaussian)energy terms,in a linear fashion into RSF(region-scalable fit-ting)model,improving the adaptive ability of the model.Secondly,a new local grayscale measure is proposed,which is combined with local kernel function to improve the local energy term.It can improve the sensitivity of the model at the weak edge,and accurately locate the target boundary.Experimental results show that this model can automatically set the initial contour and effectively retain the target edge details.Visual and quantitative experimental re-sults show that this model is superior to some mainstream active contour models.

关 键 词：视觉显著性检测 自适应符号函数 局部灰度测度 主动轮廓模型 图像分割 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]