Image Edge Detection Based On Mathematical Morphology In The Iris Location In The Study

Edge detection is one of important issues in image processing and analysis. Edge detection is a research hotspot in the field of image processing and still not been satisfactorily resolved. Mathematical morphology is a new theory in the field of image processing and pattern recognition. It is built on the basis of set theory. Its basic idea is to use a certain form of structural elements to measure and extract the shape of the corresponding image in order to achieve image analysis and identification purpose. It has the advantages of good anti-noise, computing simple, parallel computing and easy hardware implementation. So, this work will be worth studying.Two adaptive morphological edge detection methods based on different definition of the distance have been proposed. The two methods all have three steps: First, we use the optional threshold translate the gray image into binary. Second, four direction structural elements with the size of 3×3 are chosen and their weights are adaptive calculated. Finally, we use the morphological operator to detect image edge. The proposed methods alleviate the outstanding contradiction between anti-noise ability and accurate performance. It also solves the real-time calculation problem of structural elements weight. The adaptive method is extended to two-scale. In Visual C++6.0 environment, we develop a simulation system that can meet the simulation requirements of morphological edge detection.Finally, the proposed morphological edge detection method has been applied to iris location. Two iris location methods based on morphological edge detection are proposed. One is the small parameters search area method based on Hough transform, another is the minimum variance method. Experimental results show that the two methods have faster calculated speed and accurate performance than common methods.