Method of extracting crimping wheels based on two-stage ant colony algorithm

Abstract

The invention belongs to the technical field of iris diagnosis, and in particular relates to a method for extracting crimping wheels based on a two-stage ant colony algorithm; the method needs to be iterated twice, and the task of the first stage is to use a large number of artificial ants to perform a few iterations to determine the ANW Approximate position, which is used to determine the initial position of the artificial ants in the next stage; in the second stage, a small number of artificial ants are used to perform multiple iterations to obtain the final extraction result of the crimping wheel. In the process of each iteration, the artificial ants can quickly approach the ANW direction by introducing the local direction guidance factor and the global direction guidance factor; by using the pheromone update strategy based on the point density, the pheromone concentration near the edge of the ANW can be Rapid growth, and finally extract the final ANW curve according to the concentration value of pheromone.

Description

technical field [0001] The invention belongs to the technical field of iris diagnosis, and in particular relates to a method for extracting crimping wheels based on a two-stage ant colony algorithm. Background technique [0002] In iris diagnostics, the iris curl wheel is an important diagnostic sign. It is located on the periphery of the intestinal ring and is a ring-shaped line that divides the iris into two parts: the pupil in the center and the ciliary body in the periphery. It is composed of blood vessels and nerves, representing the visceral autonomic nervous system (sympathetic and parasympathetic) in the human nervous system, and it can display a lot of information related to the intestinal tract and visceral nerves. When the edge of the crimping wheel is abnormal, such as expanding or contracting, it indicates that the function of the human intestinal tract is abnormal. Therefore, whether the human intestinal tract is healthy can be known by detecting the change of...

AI Technical Summary

Problems solved by technology

[0003] Due to the complex texture of the edge of the crimping wheel, traditional methods such as edge detection operator Canny operator, Prewitt operator, Roberts operator, and edge tracking cannot extract the edge of the crimping wheel well.

For the extraction of such complex edges, literature [M.Kass, A.Witkin, D.Terzopoulous, Snakes: active contour models, in: Proceedings of the First International Conference on Computer Vision, IEEE Computer Society Press, London, 1987, pp.259 -268.] A method for extracting crimping wheels based on the improved Snake model is proposed, which overcomes the shortcomings of the traditional Snake model, such as slow convergence speed and the iterative effect being too dependent on the selection of the initial snake point position. The extraction effect of the iris image with clearer edge of the wheel is better, but when the outline of the edge of the curling wheel is blurred or incomplete, there will be errors between the extracted curling wheel and the real edge

In fact, the edge contour of the iris crimping wheel is often not very clear and discontinuous, so for this kind of crimping wheel, the effect of using this method to extract the crimping wheel is not very ideal

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