Abstract An improved mean shift segmentation approach for natural images is presented. And its application to object detection in viewbased navigation is proposed. In the improved segmentation, the color bandwidth derived from data analysis for clustering is estimated according to the image data. The density of each pixel is calculated based on the estimated bandwidth, and the local modes are searched by the direct density search way. Then a global standard for local mode merging is applied to get the final segmentation result. In its application to object detection, the object models constructed offline are used to verify the possible objects among the segmented regions. The experimental results indicate that the propesed approach can effectively detect the natural objects under complex backgrounds.
HONG YiPing,YI JianQiang,ZHAO DongBin等. Segmentation Approach for Natural Images and Application to Object Detection in ViewBased Navigation[J]. , 2006, 19(5): 658-662.
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2006, Vol. 19 
