Color and Shape Content Based Image Classification using RBF Network and PSO Technique: A Survey

The improvement of the accuracy of image query retrieval used image classification technique. Image classification is well known technique of supervised learning. The improved method of image classification increases the working efficiency of image query retrieval. For the improvements of classifica...

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Veröffentlicht in:International journal of computer science and information security 2013-11, Vol.11 (11), p.46-46
Hauptverfasser: Pandey, Abhishek, Deen, Anjna Jayant, Pandey, Rajeev
Format: Artikel
Sprache:eng
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Zusammenfassung:The improvement of the accuracy of image query retrieval used image classification technique. Image classification is well known technique of supervised learning. The improved method of image classification increases the working efficiency of image query retrieval. For the improvements of classification technique we used RBF neural network function for better prediction of feature used in image retrieval. Colour content is represented by pixel values in image classification using radial base function(RBF) technique. This approach provides better result compare to SVM technique in image representation. Image is represented by matrix though REF using pixel values of colour intensity of image. firstly we using RGB colour model. In this colour model, the authors use red, green and blue colour intensity values in matrix. SVM with partical swarm optimization for image classification is implemented in content of images which provide better Results based on the proposed approach are found encouraging in terms of color image classification accuracy.
ISSN:1947-5500