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Iris Recognition-based Security System with Canny Filter | ||
| IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING | ||
| Article 1, Volume 15, Issue 3, 2015, Pages 38-46 | ||
| Author | ||
| Dr. Hassan Jaleel Hassan | ||
| Abstract | ||
| Abstract – Image identification plays a great role in industrial, remote sensing, and military applications. It is concerned with the generation of a signature to the image. The human iris recently has attracted of biometric-based identification and verification research and development community. This iris is so unique that no two irises are alike, even among identical twins in the entire human population. In this work we propose a security system based on Iris biometric feature extraction. The focus was on the eye image, which is devoid of the eyelid and eyelashes that is done by using a camera which has the ability to show the iris with white background (eye sclera) only, using a proper position of eye on camera. The system automatically acquires the biometric data in numerical format (Iris images) by using a properly located sensor. We are considering camera as a high quality sensor. Iris images are typically color images that are analyzed to three bands monochrome images (Red, Green, and Blue). Each band of monochrome image represents a grey scale image. Then the feature extraction algorithm is used to detect Iris Effected Region (IER) for each monochrome image, and then extract features from IER that are numerical characterization of the underlying biometrics. Later we identify the authorized person by comparing the features obtained from the feature extraction algorithm with the previously stored features by producing a similarity score. This score indicates the degree of similarity between a pair of biometrics data under consideration. Depending on degree of similarity, authorized person can be identified. A successful identification rate of 100% was achieved for ten person iris images. | ||
| Keywords | ||
| Security System; Iris Pattern recognition; Feature extraction; Biometric Identification | ||
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