Iris Image Error Correction Techniques
| Autor: | Olive Teresa, Shruti Sekar, Prashanthi, Sarah, J. Jenkin Winston |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Deblurring
Biometrics urogenital system business.industry Computer science Noise reduction fungi Iris recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition White noise urologic and male genital diseases Iris flower data set female genital diseases and pregnancy complications ComputingMethodologies_PATTERNRECOGNITION medicine.anatomical_structure medicine cardiovascular diseases Artificial intelligence Iris (anatomy) business Error detection and correction ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | 2019 2nd International Conference on Signal Processing and Communication (ICSPC). |
| DOI: | 10.1109/icspc46172.2019.8976522 |
| Popis: | In today's world, security has gotten paramount. Many biometric methods like facial expression recognition system and Iris recognition system have been developed. Iris biometry helps in identifying an individual in a more intuitive and natural manner. Iris recognition focuses on recognizing the identity of individuals using the textural based characteristics. But, due to various reasons corruption of texture features of iris often occurs during denoising and deblurring. In this paper we propose maltlab algorithms to overcome these defects as well as extract the features to receive a defect less image. To verify the algorithm white noise is added to the iris dataset and the calculations are done as required. This process shows that denoising and deblurring can improve the quality of the iris image evidently. |
| Databáze: | OpenAIRE |
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