In this paper, a new method based on the class-based histogram equalization to compensate the acoustic mismatch between training and test conditions of speech recognizers is proposed. The proposed method improves the speech recognition accuracy in noisy environments by reducing two limitations of the conventional histogram equalization: The discrepancy of phonetic class distributions between tr...

A multiple kernel fusion method combining two multiresolution histogram face descriptors is proposed to create a powerful representation method for face recognition. The multi resolution histogram descriptors are based on local binary patterns and local phase coding to achieve invariance to various types of image degradation. The multikernel fusion is based on the computationally efficient spec...

Character segmentation is the major step of document image analysis and optical character recognition (OCR). The character segmentation is necessary to detect all the character regions in the image document. The proposed method preprocesses the image document with edge detection techniques to enhance the character edges. Further, the watershed algorithm is implemented to identify the regions of...

This paper presents new methods for efficient object tracking in video sequences using multiple features and particle filtering. A histogram-based framework is used to describe the features. Histograms are useful because have the property that they allow changes in the object appearance while the histograms remain the same. Particle filtering is used because it is very robust for non-linear and...

We propose a novel information-processing algorithm called Vector Quantization (VQ) codebook space information processing. Based on this algorithm, we have developed a very simple yet highly reliable face recognition method called VQ histogram method. General codebook consisting of 33 low-frequency patterns for VQ processing is created by theoretical method. Codevector referred (or matched) cou...

A new class-based histogram equalization method is proposed for robust speech recognition. The proposed method aims at not only compensating for an acoustic mismatch between training and test environments but also reducing the two fundamental limitations of the conventional histogram equalization method, the discrepancy between the phonetic distributions of training and test speech data, and th...

20 ABSTRACT Enhancement of human vision to get an insight to information content is of vital importance. The traditional histogram equalization methods have been suffering from amplified contrast with the addition of artifacts and a surprising unnatural visibility of the processed images. In order to overcome these drawbacks, this paper proposes interative, mean, and multi-threshold selection c...