Speech compression, enhancement and recognition in noisy, reverberant conditions is a challenging task. In this paper a new approach to this problem, which is developed in the framework of probabilistic random modeling. speech coding techniques are commonly used in low bit rate analysis and synthesis . Coding algorithms seek to minimize the bit rate in the digital representation of a signal wit...

This paper presents a Lossy image compression technique which is combination of discrete wavelet transform (DWT), Thresholding, Vector Quantization (VQ) and Huffman coding. Proposed method is as follows, First, DWT is performed on the original image then Globle Thresholding technique is applied and resulting coefficients are then vector quantized. VQ indices are Huffman coded to increase the co...

In this paper, we propose a new approach for optimization in audio watermarking using artificial intelligent technique. The watermarks are embedded into the low frequency coefficients in discrete multiwavelet transform domain. The embedding technique is based on quantization process which does not require the original audio signal in the watermark extraction. We have developed an optimization t...

Mesh chartification is an important tool for processing meshes in various applications. In this paper, we present a novel feature sensitive mesh chartification technique that can handle huge meshes with limited main memory. Our technique adapts the mesh chartification approach using Lloyd-Max quantization to out-of-core processing. While the previous approach updates chartification globally at ...

Audio coding based on Frequency Domain Linear Prediction (FDLP) uses autoregressive models to approximate Hilbert envelopes in frequency sub-bands. Although the basic technique achieves good coding efficiency, there is a need to improve the reconstructed signal quality for tonal signals with impulsive spectral content. For such signals, the quantization noise in the FDLP codec appears as freque...

Novel algorithms for vector quantization codebook design are presented in this paper. Two basic techniques are proposed. The first technique takes into consideration specific characteristics of the blocks of the training sequence during the generation of the initial codebook. In this way a representative initial codebook is generated. Starting from a high quality initial codebook the iterative ...

The present paper proposes a novel approach for facial expression identification based on the statistical features extracted from the 4-bit co-occurrence matrix. In the present, first color image is converted into grey level image using 7-bit quantization technique. To reduce the complexity of the Grey Level Co-occurrence matrix the present paper generates the co-occurrence matrix on 4 bit grey...

Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for distributed optimization and control. BFOA is inspired by the social foraging behavior of Escherichia coli. BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application dom...

This paper presents a matching pursuits sinusoidal speech coder which incorporates new techniques including a novel vector quantization (VQ) technique used for the weighted quantization of spectral magnitude vector, and an interframe quantization of spectral magnitudes using an interpolation matrix that minimize the weighted interpolation error. The paper describes a novel vector quantization t...

In this work we propose an efficient technique to quantize the immitance spectral frequency (ISF) in an algebraic code-excited linear prediction (ACELP) wideband codec. The Constrained Voicing-Based Vector Quantization (C-VBVQ) presented in this paper improves substantially the performance of the unconstrained-VBVQ approach for both clean and noisy speech. Both techniques reduce the codebook se...