A Hybrid Algorithm of Otsu and Adaptive Region for Image Segmentation

The traditional Region Growing (RG) algorithm is a semi-automatic image segmentation algorithm that requires manual selection of seed points, manual setting of thresholds, which may cause the cavity and over-segmentation while deals with the uneven and undivided image for noise and grayscale. Therefore, the classical Otsu method is adopted to find the optimal threshold in HSV space to obtain the initial binarized segmentation image. Then, the Adaptive Region Growing (ARG) algorithm is applied to find the image edge. To be specific, the initial seed point is confirmed automatically through histogram firstly. Secondly, the threshold of growth condition is determined according to the average similarity of image. Finally, the image is grown into the contour edges. This image is mixed together with the initial Otsu segmentation image can obtain the final processed image. Experimental results show that the proposed algorithm has strong anti-interference, which can effectively reduce the mis-segmentation rate.