光学精密工程2013，Vol.21Issue(2)：531-538,8.DOI:10.3788/OPE.20132102.0531
视觉显著目标的自适应分割
Adaptive segmentation for visual salient object
摘要
Abstract
On the basis of a visual attention model and a maximum entropy segmentation method, an adaptive segmentation method was proposed to segment the object from a complex background in the scene image and to detect a salient object effectively and accurately. First, the feature of original image was extracted via four channels on color, intensity, orientation and local energy. The profile of object feature was described more accurately by combining the channel of local energy with a simple biologically-inspired model. Then, object detection masks were constructed to remove background gradually according to the gray intensity of the pixels in the saliency map. By taking blend masks with the original image as a pre-segmentation result, the entropy of pre-segmentation images was computed. Finally, the entropy of salient object was estimated via maximization information entropy principle and the optimized image extraction for the salient object was obtained by estimating the relationship of entropy between salient object and masks in the saliency map. Experimental results indicate that the salient object detected by proposed method is more integrity, the F-measure of segmentation performance is 0.56, and the precision ratio and the recall ratio of detection are 0.69 and 0.41, respectively. The proposed method is more reasonable and effective than the traditional method, and it can satisfy the requirements of detecting the salient objects from complex backgrounds.关键词
视觉显著目标/局部能量/目标检测/最大熵准则/自适应分割Key words
visual salient object/ local energy/ object detection/ maximization entropy/ adaptive segmentation分类
信息技术与安全科学引用本文复制引用
赵宏伟,陈霄,刘萍萍,耿庆田..视觉显著目标的自适应分割[J].光学精密工程,2013,21(2):531-538,8.基金项目
国家自然科学基金资助项目(No.61101155) （No.61101155）
吉林省科技发展计划资助项目(No.20101504) （No.20101504）
