An efficient iris image thresholding based on binarization threshold in black hole search method

In iris recognition system, the segmentation stage is one of the most important stages where the iris is located and then further segmented into outer and lower boundary of iris region. Several algorithms have been proposed in order to segment the outer and lower boundary of the iris region. The aim of this research is to identify the suitable threshold value in order to locate the outer and lower boundaries using Black Hole Search Method. We chose these methods because of the ineffient features of the other methods in image indetification and verifications. The experiment was conducted using three data set; UBIRIS, CASIA and MMU because of their superiority over others. Given that different iris databases have different file formats and quality, the images used for this work are jpeg and bmp. Based on the experimentation, most suitable threshold values for identification of iris aboundaries for different iris databases have been identified. It is therefore compared with the other methods used by other researchers and found out that the values of 0.3, 0.4 and 0.1 for database UBIRIS, CASIA and MMU respectively are more accurate and comprehensive. The study concludes that threshold values vary depending on the database