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

Source: [Color and Shape Content Based Image Classification using RBF Network and PSO Technique: A Survey](<https://www.sota2.com/research/paper/68fa612c1e209131ce9f2f6f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T19:54:34.816Z

Authors: Abhishek Pandey, Anjna Jayant Deen, Rajeev Pandey

Published: 2013-11-27T07:14:25.000Z

## Abstract

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 RBF using pixel values of colour intensity of image. Firstly we using RGB colour model. In this colour model we 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1311.6881>)

[PDF](<https://arxiv.org/pdf/1311.6881.pdf>)