DWT and DCT Based Robust Iris Feature Extraction and Recognition Algorithm for Biometric Personal Identification
Human iris is one of the most reliable biometric because of its uniqueness, stability and noninvasive nature. Thus it has attracted the attention of biometrics based identification and verification research and development community. In this paper, a new approach of iris image feature extraction technique based on the statistical properties of Discrete Cosine Transform (DCT) domain is proposed. A Canny Edge Detection followed by Hough Transform is used to detect the iris boundaries in the eye's digital image. The two level Discrete Wavelet Transformation (DWT) is applied on the segmented and normalized iris region. Both second level horizontal and vertical detail sub-bands are used for encoding unique iris feature.