Human Iris Localization Combined with Ant Colony and Improved Hough Circle Detection

When the traditional Hough transform based on circl e detection locates the human iris, it involves a three-dimensional paramet er space, so there is a shortage of computational time and space overhead. Aiming at th is problem, a Hough transform circle detection algorithm using gradient to reduce the sp atial dimension of parameters is proposed. Firstly, the image is preprocessed by mat hematical morphology to reduce noise and eyelash interference. Secondly, the ant colony optimization algorithm is used to preprocess the image. Edge extraction is performed to reduce the number of points participating in the Hough transform. Finally, the improved Hough transform is used to locate the iris. The high-quality and low-quality i mages are used to compare the traditional Hough transform method and the literature [13] meth od. The results show that the method not only improves the positioning speed, but also i mproves the positioning accuracy. Compared with other methods, the image quality is i mproved. The requirements are also significantly reduced.