Artificial Neural Network Based Visual Recognition System using Dwt for Hearically Impaired Person
Y. M. Gaikwad1, K. N. Pawar2
1Y. M. Gaikwad, M.E. Appear, Department of Electronics Engineering, S.S.V.P.S. B.S.D. C.O.E, Dhule, India.
2K. N. Pawar, Head, Department of Electronics Engineering, S.S.V.P.S. B.S.D. C.O.E, Dhule, India.
Manuscript received on May 21, 2014. | Revised Manuscript received on June 16, 2014. | Manuscript published on June 30, 2014. | PP: 308-310 | Volume-3, Issue-5, June 2014. | Retrieval Number: E3238063514/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Generally image processing is done to process an image for different application. There is variety of transform base feature extraction method. Visual recognition system or lip reading method is important generally in noisy condition. The new modality in image processing area is gives you dictation of voice. The discrete cosine transforms (DCT) and discrete wavelet transform (DWT) are techniques for converting a signal into elementary frequency components. These are widely used in image compression. Here we develop some functions to compute the DWT and to compress images. These functions illustrate the power of Mathematic in the prototyping of image processing algorithms. The rapid growth of digital imaging applications, including desktop publishing, multimedia, teleconferencing, and high-definition television (HDTV) has increased the need for effective and standardized image compression techniques.
Keywords: ANN, DCT, DWT, HMM.