Image segmentation algorithm for reconstruction labeling watershed in color space
基于彩色模型的重构标记分水岭分割算法

The watershed algorithm is a powerful morphological tool for image segmentation,but the traditional watershed algorithm causes serious over-segmentation if the actual image is affected by specularities and shadows. To solve these problems,a new image segmentation,based on reconstruction labeling watershed algorithm in color space,is proposed. First,the RGB color image is converted to a new color space image. The directions that are not influenced by specularities and shadows are extracted to calculate their gradients. Then,object regions are extracted by using the morphological opening and closing to compose a binary marked image,and the gradient image is introduced to substitute the marked image. Finally,the watershed transformation is employed to the modified gradient image. The new algorithm cannot only overcome over-segmentation,which is produced by texture details and noise,but also can suppress over-segmentation caused by specularities and shadows. Moreover,the segmentation algorithm is executed on a primitive gradient image instead of filtering and simplified image,so the object's edge information is retained greatly. Theory analysis and experimental results have shown the segmentation algorithm is effective.