A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Kamra, Amit
- A New Method for Image Denoising Based on Multiresolution Technique
Authors
1 IET, Bhaddal, Punjab, IN
2 GNE, Ludhiana, Punjab, IN
Source
Digital Image Processing, Vol 2, No 10 (2010), Pagination: 371-375Abstract
The need for image denoising is encountered in many practical applications. The problem with the data acquisition process, imperfect instruments and interfering natural phenomena can all degrade the data of interest. Noise can also be introduced by transmission errors. Thus it is necessary to apply an efficient denoising technique to compensate for such data corruption. The multiresolution technique i.e. curvelet transform has been employed as an efficient method in image denoising. The two phases for curvelet transform are analysis (decomposition) and synthesis (reconstruction). In the present work, a new denoising technique using hard threshold has been proposed and the results are compared with the other state of art noise reduction methods. The experimental results show that the new method is better than the other noise reduction methods in terms of quality metrics like MSE, PSNR and SSIM and reduces the Gaussian noise significantly while preserving features at the boundary of the image.Keywords
Image Denoising, Curvelet Transform, FDCT, Universal Threshold and Noise Variance.- Recognition of Audiovisual Celebrity in Unrestrained Web Videos
Authors
1 Padhiana, Distt: Jalandhar, Punjab, IN
2 GNDEC, Ludhiana, Punjab, IN
Source
Data Mining and Knowledge Engineering, Vol 2, No 3 (2010), Pagination: 59-62Abstract
A number of video clips are available online. Users are uploading videos and provides the source of indexing information as title of video and set of keywords. Automated extraction of video content from a large scale video is a challenging and yet unsolved problem. Proposed method finds the audiovisual mapping. All pieces of information is trained automatically without any human supervision. We presents the results in 1200 videos and show the effectiveness of the method per celebrity basis.Keywords
Speaker Recognition, Face Recognition, Diagonal Covariances, Equal Error Rates.- A New Method for Fingerprint Core Point Detection based upon Orientation Field
Authors
1 Guru Nanak Dev Engineering College, Ludhiana, IN
Source
Biometrics and Bioinformatics, Vol 2, No 11 (2010), Pagination: 327-330Abstract
Singular point detection is the most important task of fingerprint image classification operation. Two types of singular points called core and delta points are claimed to be enough to classify the fingerprints. The classification can act as an important indexing mechanism for large fingerprint databases which can reduce the query time and the computational complexity. There already exists many singular point detection algorithms, Most of them can efficiently detect the core point when the image quality is fine, but when the image quality is poor, the efficiency of the algorithm degrades rapidly. In the present work, a new method of detection and localization of core points in a fingerprint image is proposed.
Keywords
Core Point, Delta Point, Orientation Field.- A Novel Method for Fingerprint Feature Extraction
Authors
1 RBIEBT, Sahuran, Punjab, IN
2 GNE, Ludhiana, IN
3 Sant Baba Bhag Singh, Hoshiarpur, IN