We report on a hierarchical nearest-neighbor classiier algorithm which we conceived for the recognition of handwritten characters. Distances to all classes are used both as a decision criterion in the classiication hierarchy and for generating class membership coeecients. These likelihood values can be easily integrated in a multi-agent cognitive environment. We introduce a new completely binar...

A new approach to the design of optimised codebooks using vector quantisation (VQ) is presented. A strategy of reinforced learning (RL) is proposed which exploits the advantages offered by fuzzy clustering algorithms, competitive learning and knowledge of training vector and codevector configurations. Results are compared with the performance of the generalised Lloyd algorithm (GLA) and the fuz...

Vector quantisation (VQ) is a method widely used in low bit-rate coding and transmission of speech signals. Unfortunately, a single bit error in the transmitted index, due to noise in the transmission channel, could degrade perceived speech quality at the receiver quite dramatically, as the reference vector retrieved by the corrupted index may di er greatly from the vector corresponding to the ...

Vector quantisation (VQ) is a method widely used in low bit-rate coding and transmission of speech signals. Unfortunately, a single bit error in the transmitted index, due to noise in the transmission channel, could degrade perceived speech quality at the receiver quite dramatically, as the reference vector retrieved by the corrupted index may di er greatly from the vector corresponding to the ...

In this paper, we describe a novel approach to image quantisation by using a genetic algorithm to find near-optimal code words. Moving away from the traditional binary string representations of genetic data, the proposed system applies genetic operators directly on pixel blocks thus avoiding any conversion to a conventional format. To operate on the data this way, operators for fitness, combina...

The development of a pattern recognition architecture based on vector quantization techniques is presented which is applied to the recognition of handwritten bank forms. After an overview of nearest-neighbor classiication and clustering, a fast completely binary version of the k-means algorithm is introduced and results for large character databases are given. An integration of these methods in...

Over the last couple of decades, more and more presentations are done on computer screen. The need to store or broadcast such presentation efficiently is in high demand across different application areas. This paper proposes a screen capture representation called vector quantisation. This system captures sequence of actions on a computer screen and minimizes its video file size for storage. It ...

This study considers linear filtering methods for minimising the end-to-end average distortion of a fixed-rate source quantisation system. For the source encoder, both scalar and vector quantisation are considered. The codebook index output by the encoder is sent over a noisy discrete memoryless channel whose statistics could be unknown at the transmitter. At the receiver, the code vector corre...

We present a novel method of image expansion using vector quantisation. The algorithm is inspired by fractal coding and uses a statistical model of the relationship between details at different scales of the image to interpolate detail at one octave above the highest spatial frequency in the original image. Our method aims at overcoming the drawbacks associated with traditional approaches such ...