Data compression for image recognition using neural network

A novel data compression algorithm utilizing the histogram and the high-capacity exponential bidirectional associative memory (eBAM) is presented. Since eBAM has been proved to possess high capacity and fault tolerance, it is suitable to be utilized in the data compression using the table-lookup scheme. The histogram approach is employed to extract the feature vectors in the given data. The result of the simulation of the proposed algorithm turns out to be better than the traditional methods.

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Data compression for image recognition using neural network

Cited by 2 publications

References 5 publications

Image compression using hybrid neural networks combining the auto-associative multi-layer perceptron and the self-organizing feature map

Image compression using hybrid neural networks combining the auto-associative multi-layer perceptron and the self-organizing feature map

Data compression by the recursive algorithm of exponential bidirectional associative memory

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