A Review Paper on a Genetic Algorithm Applied to Content-Based Image Retrieval for Natural Scenes Classification

The Content-Based Image Retrieval (CBIR) techniques use different techniques retrieve self-content descriptors over the image data set being studied according to the type of the image. The reason of study of CBIR consists in classifying images avoiding the use of manual labels related to understanding of the image by the human being vision. In this work provide a new CBIR procedure which works with local texture analysis, and which is developed in a non-supervised fashion, clustering the local achieved descriptors and classifying them with the use of a K-means algorithm supported by the genetic algorithm. This method has been deployed in LabVIEW software, programming each part of the procedure in order to implement it in hardware. The results are very promising, reaching up to 90% of recall for natural scene classification.