The Comparison of Iris Detection Using Histogram Equalization and Adaptive Histogram Equalization Methods. (March 2019) - Mustaghfirin, Fathan; Erwin,; Kesuma Putra, Hadrians; Yanti, Umi; Ricadonna, Rahma
Abstract: This paper presents a comparison between two image improvement techniques, Histogram Equalization (HE) and Adaptive Histogram Equalization (AHE). Canny edge detection is used as a comparison. The HE method is a contrast enhancement method that is designed to be widely applied and has effectiveness in image improvement that will be carried out by segmentation, while AHE is more effective to be applied to images that aim to recognize patterns. Performance measurement using a peak signal to noise ratio (PNSR) produces an average value of 16.76 for the HE method and for the AHE method for 16.95. Before the edge detection process, the image of the iris is done by the compression stage using discrete wavelet transform. Average compression ratio for all tested iris datasets is 1.27