PERBAIKAN KUALITAS CITRA IRIS MATA MENGGUNAKAN METODE HISTOGRAM EQUALIZATION, ADAPTIVE HISTOGRAM EQUALIZATION DAN OPERASI MORFOLOGI
Daftar Isi:
- The iris pattern is unique to each eye subject and remains stable throughout life. Iris is known as the most accurate and reliable part of one's identification. During the data acquisition process, the iris image dataset that the author uses is unbalanced contrast and noise in the form of light reflection. To overcome this problem, it is necessary to improve the quality of the image so that the image is easier to analyze by the image-based automation process. The method used in the image enhancement process in this study is histogram equalization (HE) and Adaptive Histogram Equalization (AHE). Histogram equalization serves to balance contrast and minimize noise found in the iris image that I use. Contrast enhancement HE can change the brightness thoroughly which results in low saturation or excessive saturation in certain parts. AHE improves the shortcomings of HE by increasing contrast locally or in certain parts in more detail. In addition to improving image quality, morphological image processing techniques are also used. Methods Morphological operations function as a method that will eliminate noise found in the iris image. The results of the histogram equalization method, adaptive histogram equalization and morphological operations will be measured the image quality value using the Peak Signal Noise Ratio (PSNR) measurement method.