Abstract: Image co-segmentation is one of the active research areas in computer vision.The ability to utilize the information of similar objects in segmentation process is one of the advantages of co-segmentation,which is different from other segmentation methods.Meanwhile,establishing the similarity of corresponding objects is becoming a challenging task.This paper presented a novel consistency of center sensitive histogram for image co-segmentation.Unlike the traditional image histogram that calculates the frequency of occurrence for the intensity value by adding ones to the corresponding bin,a consistency of center sensitive histogram is computed at each pixel and a floating-point value is added to the corresponding bin for each occurrence of the intensity value.The floating-point value is a spatial consistency between the pixel of occurrence of intensity and the pixel where the histogram is computed.Therefore,the histogram not only takes the distribution of each pixel’s intensity value into account,but also the spatial relative position.A robust co-segmentation framework was proposed.Its robustness reflectsthe similar objects under different illumination and deformation condition can be both segmented well.The proposed technique was verified on various test image data sets.The experimental results demonstrate that the proposed method outperforms the average of state-of-the-art 3%,especially when the test image is in different illumination conditions and has different shapes.

Key words: Consistency of center, Co-segmentation, Deformation, Histogram, Illumination invariant