Study On Iris Pigmentation Spot Automatic Positioning

Iris Diagnostics is a method to check with the iris to determine organ disease exists in other parts of the body, and the damage location or functional disorders. By looking at the different locations of the abnormal changes we can make a diagnosis of diseases of certain organs, such as: iris pigment spot appears shows a certain brain abnormalities, concave area around the pupil shows an ulcer disease, even strong feeling of pain disorders, which are diagnostic theoretical basis for the iris. By observing the human iris characteristics, including depression, spots, cracks, lines, color and density changes, combined with the principle of the iris reflection map, we can observe the body tissue, organs, each system, and the endocrine glands of the recession, obstacles and its possible future development. Therefore, accurate extraction of useful information and eye iris lesion automatic diagnostic feature location is an important part of the iris diagnose, extraction and location directly affects the positioning accuracy of the diagnostic progress. This paper analyzes the current status of the iris disease diagnosis research and found that the existing iris diagnosis is still in its infancy, there is no complete diagnostic system to achieve its key technical problem and the key is automatic iris disease trillion feature extraction and quantification. This paper will start to solve some existing problems, such as the acquisition of the iris image, iris information to solve the way of effective extraction, and the characteristics of iris disease trillion in pigmentation spots in the exact location. Propose a method to determine the point within the local area the size of shades of gray to find the true edge points of iris segmentation, first locate the center of the pupil, and then horizontal scan in the local area to determine the contours of a candidate set of points, with appropriate convolution template to calculate the gradient of candidate pixel concentration gradient on the direction perpendicular to the edge of the largest point, and track the maximum gradient point by point, the edge of the pupil and iris edge repeated twice, can get a complete outline of the iris. Another step is using the method of minimum gray pigmentation spots and effective positioning. Light gray pigmentation spots distribution characteristics, in order to spot and the surrounding pixels based on the difference between the gray, the image center by region and pixel values of boundary points of comparison, in line with the gray value is less than the edge of the central region part of the gray values of the characteristics determined for the pigmentation spots. And apply software designed in this paper to prove the algorithm in practice, the effectiveness and feasibility. In order to realize computer automatic extraction, recognition and matching of the disease characteristics, the paper will provide some theoretical support.