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Deshpande, Anand
- Segmentation and Quality Analysis of Long Range Captured IRIS Image
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Angadi Institute of Technology and Management, IN
2 Department of Electronics and Communication Engineering, Gogte Institute of Technology, IN
1 Department of Electronics and Communication Engineering, Angadi Institute of Technology and Management, IN
2 Department of Electronics and Communication Engineering, Gogte Institute of Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 6, No 4 (2016), Pagination: 1280-1283Abstract
The iris segmentation plays a major role in an iris recognition system to increase the performance of the system. This paper proposes a novel method for segmentation of iris images to extract the iris part of long range captured eye image and an approach to select best iris frame from the iris polar image sequences by analyzing the quality of iris polar images. The quality of iris image is determined by the frequency components present in the iris polar images. The experiments are carried out on CASIA-long range captured iris image sequences. The proposed segmentation method is compared with Hough transform based segmentation and it has been determined that the proposed method gives higher accuracy for segmentation than Hough transform.Keywords
Segmentation, Quality Score, Long Range Iris Images.
- Single Frame Super Resolution of Noncooperative IRIS Images
Abstract Views :180 |
PDF Views:3
Authors
Affiliations
1 Department of Electronics and Communication Engineering, Angadi Institute of Technology and Management, IN
2 Department of Electronics and Communication Engineering, Gogte Institute of Technology, IN
1 Department of Electronics and Communication Engineering, Angadi Institute of Technology and Management, IN
2 Department of Electronics and Communication Engineering, Gogte Institute of Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 7, No 2 (2016), Pagination: 1362-1365Abstract
Image super-resolution, a process to enhance image resolution, has important applications in biometrics, satellite imaging, high definition television, medical imaging, etc. The long range captured iris identification systems often suffer from low resolution and meager focus of the captured iris images. These degrade the iris recognition performance. This paper proposes enhanced iterated back projection (EIBP) method to super resolute the long range captured iris polar images. The performance of proposed method is tested and analyzed on CASIA long range iris database by comparing peak signal to noise ratio (PSNR) and structural similarity index (SSIM) with state-of-the-art super resolution (SR) algorithms. It is further analyzed by increasing the up-sampling factor. Performance analysis shows that the proposed method is superior to state-of-the-art algorithms, the peak signal-to-noise ratio improved about 0.1-1.5 dB. The results demonstrate that the proposed method is well suited to super resolve the iris polar images captured at a long distance.Keywords
Super Resolution, Iterated Back Projection, Iris Recognition, SSIM, PSNR.- Survey of Super Resolution Techniques
Abstract Views :195 |
PDF Views:0
Authors
Affiliations
1 Department of Electronics and Communication Engineering, Angadi Institute of Technology and Management, IN
2 Department of Electronics and Communication Engineering, Gogte Institute of Technology, IN
1 Department of Electronics and Communication Engineering, Angadi Institute of Technology and Management, IN
2 Department of Electronics and Communication Engineering, Gogte Institute of Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 9, No 3 (2019), Pagination: 1927-1934Abstract
The key objective of super-resolution imaging is the process of reconstructing a high resolution image from one or a set of low resolution images, to overcome the ill-posed conditions of the image capturing process to get better visualization. It has found practical applications in many real world problems such as surveillance, medical imaging, text image analysis, biometrics, satellite imaging, to name a few. This has encouraged many researchers to develop a new super resolution algorithm for a particular purpose. The objective of the review paper is to explore the different image super resolution algorithms used to enhance the low resolution images to high resolution images. This survey on super resolution algorithms will help the researchers to comprehend the effectiveness of the super resolution process and will make easy to develop advanced super resolution methods.Keywords
Super Resolution, PSNR, Frequency Domain, Gaussian Process Regression, Total Variation.References
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