用于显微细胞图象的二维自适应阈值分割算法的优化

为了改善细胞图象的分割效果 ,考虑将二维自适应阈值分割算法应用于显微细胞图象的分割 .针对细胞图象的二维直方图特点和分割要求 ,在对传统二维阈值分割算法进行优化和简化的基础上 ,通过改变阈值取值范围、优化阈值搜索方法等措施 ,提出了一种快速实现细胞图象二维自适应阈值分割算法 .仿真结果表明 ,新算法与传统算法相比 ,不仅大大减少了计算复杂性 ,同时还使分割效果得到了一定程度的改善

Improvement of Two-dimension Adaptive Thresholding Segmentation Algorithm for Microscopic Cellular Images

Two dimension adaptive threshold segmentation algorithm applied to the segmentation of microscopic cellular image is considered in order to improve the result of segmentation. Based on the characteristic of two dimension histogram of microscopic cellular image and the require of segmentation, one of the two dimension is the pixel's gray value and the other is its neighboring average gray value. usually. at the positions of target or background, gray value of pixel and its neighboring average gray are similar; at the edge of target and background, gray value of pixel and its neighboring average gray are very different, so the pixels of target and background will appear around the diagonal. the sections of the object and the background can being changed, at the same time changing the step's value of searching optimal threshold value, using occur times instead of probability distribution and recursive computation instead of plenty of repeat computation, the improved fast two dimension segmentation algorithms for microscopic cellular image adaptive thresholding segmentation are provided and carried. Simulation shows that the improved algorithms reduces computation complexity greatly and reduces the running time of the algorithms, and the improved algorithms has stronger power against noise and gets clearer edges of targets than original one. From simulation result for cellular image, it could be seen that the improvement and simplification are both valid.