基于彩色模型的重构标记分水岭分割算法

分水岭算法是一种适用于图像分割的强有力的形态学工具,但传统的分水岭算法存在严重的过分割现象,并且实际图像容易受到反射亮光和阴影的影响。针对该问题提出一种新的彩色空间重构标记分水岭分割算法。该算法首先将RGB彩色图像转换到新的彩色空间中,抽取不受反射亮光和阴影影响的分量进行梯度计算;然后利用形态学开闭重构提取感兴趣目标构成二值标记图像,利用标记图像修改梯度图;最后在修改的梯度图上进行分水岭变换。新算法不仅可以抑制由于纹理细节和噪声引起的过分割,还可以有效地抑制由于反射亮光和阴影产生的过分割,同时由于该分割算法是在原始梯度图上而非滤波简化的图像上进行的,因此物体的边缘信息也得以最大程度的保留。理论分析和实验结果表明了该算法的有效性。

Image segmentation algorithm for reconstruction labeling watershed in color space

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.