Zobrazeno 1 - 6
of 6
pro vyhledávání: '"K. T. Shanavaz"'
Publikováno v:
ICTACT Journal on Image and Video Processing, Vol 8, Iss 1, Pp 1588-1595 (2017)
In this paper, a multiwavelet based fingerprint compression technique using set partitioning in hierarchical trees (SPIHT) algorithm with optimised prefilter coefficients is proposed. While wavelet based progressive compression techniques give a blur
Externí odkaz:
https://doaj.org/article/0970a84be21b4156a872a893f80f050c
Publikováno v:
Materials Today: Proceedings. 24:1890-1897
Nowadays quality of the image is very important. But the images captured by cameras are affected by different atmospheric conditions such as haze, fog rain etc. These conditions adversely affect the visibility of the images and reduces the contrast.
Publikováno v:
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MICROELECTRONICS, SIGNALS AND SYSTEMS 2019.
Nowadays quality of outdoor as well as indoor images are very important. But outdoor images are deteriorated by haze, fog, rain etc. These atmosphere conditions adversely affect the visibility of the images and reduces the contrast. It is very much a
Publikováno v:
ICTACT Journal on Image and Video Processing, Vol 8, Iss 1, Pp 1588-1595 (2017)
In this paper, a multiwavelet based fingerprint compression technique using set partitioning in hierarchical trees (SPIHT) algorithm with optimised prefilter coefficients is proposed. While wavelet based progressive compression techniques give a blur
Publikováno v:
2017 International Conference on Networks & Advances in Computational Technologies (NetACT).
Speech is the natural and vocalized form of human communication. Automatic Speech Recognition makes the computer to understand what was spoken by the speaker. Power Normalized Cepstral Coefficients (PNCC) is a feature extraction technique that uses p
Publikováno v:
Journal of Mechanics in Medicine and Biology. 15:1550081
A method for automatic classification of Arrhythmias from Electrocardiogram based on features generated from a new Continuous Wavelet Transform (CWT) is presented in this paper. The classification performance was studied using the most commonly avail