| Segmentation of cell image is an important researching area in medical image processing. The diversities and complexity of cell image make it hard to reach the segmenting goal with a single method.At first, this paper introduced traditional image segmentation technology and implement as well as edge detection algorithm. This paper proposes a new digital image algorithm based on the iterative algorithm with the purpose to realize optimal threshold which is combined with the algorithm of mathematics morphological. This implementing of this method in megalinker cell segmentation brings about decent effects and further conquer the shortcomings that traditional edge detector may be easily influenced by. Various kinds of cells are compared in the use of Ostu segmentation algorithm. In order to get better segmentation results, histogram potential, which contains image spectral information, is combined with watershed growth algorithm. Compared with traditional arithmetic, the result shows that the improved method is better in keeping integrality and consistency of image, image segmentation, threshold edge detection. This dissertation expands on a new algorithm, which has the function of analyzing edge form with the chain code. By the introduction of the concepts of relative chain code and absolute chain code, this paper proposes a simple and direct algorithm to compute chain code sum (average chain code). Further more, this algorithm also provides the criterion distinguishing edge inflexion and sleek curve section and the method computing inaccurately curvature radius and approximate perimeter. The paper also introduces the use method with cell edge hollow repairing and overlap or conglutination cell segmentation. For example, this algorithm has proved high-speed and has a good effect of cell segmentation on more than twenty groups of conglutinate and absent cells which are gathered from three kinds of cells. A user's interface application program by using C++Builder is developed.
|
PDF Full Text Request