A Genetic Algorithm Applied to Content-Based Image Retrieval for Natural Scenes Classification

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Yolanda Pérez-Pimentel; Ismael Osuna-Galan; Juan Villegas-Cortez; Carlos Avilés-Cruz: A Genetic Algorithm Applied to Content-Based Image Retrieval for Natural Scenes Classification. Artificial Intelligence (MICAI), 2014 13th Mexican International Conference on, 155 - 161.




The Content-Based Image Retrieval (CBIR) techniques comprise methodologies intended to retrieve self-content descriptors over the image data set being studied according to the type of the image. The main purpose 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 we 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.

Extended Abstract


author={Y. Pérez-Pimentel and I. Osuna-Galan and J. Villegas-Cortez and C. Avilés-Cruz},
booktitle={Artificial Intelligence (MICAI), 2014 13th Mexican International Conference on},
title={A Genetic Algorithm Applied to Content-Based Image Retrieval for Natural Scenes Classification},
keywords={content-based retrieval;genetic algorithms;image classification;image retrieval;image texture;natural scenes;pattern clustering;CBIR;LabVIEW software;clustering;content-based image retrieval;genetic algorithm;image classification;k-means algorithm;local texture analysis;natural scene classification;Data mining;Feature extraction;Genetic algorithms;Image color analysis;Standards;Testing;Training;Genetic Algorithms;K-Means;LabVIEW;Natural scene CBIR},
url={http://dx.doi.org/10.1109/MICAI.2014.30 http://de.evo-art.org/index.php?title=A_Genetic_Algorithm_Applied_to_Content-Based_Image_Retrieval_for_Natural_Scenes_Classification },

Used References

José Félix Serrano-Talamantes, Carlos Avilés-Cruz, Juan Villegas-Cortez, Juan H. Sossa-Azuela: Self organizing natural scene image retrieval. Expert Systems with Applications, vol. 40, no. 7, pp. 2398-2409, 2013 http://dx.doi.org/10.1016/j.eswa.2012.10.064

Y. Liu, D. Zhang, G. Lu and W.-Y. Ma: A survey of content-based image retrieval with high-level semantics. Pattern Recogn., vol. 40, no. 1, pp. 262-282, 2007 http://dx.doi.org/10.1016/j.patcog.2006.04.045

J. Li and J. Wang, "Real-time computerized annotation of pictures", Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 30, no. 6, pp. 985-1002, 2008 http://dx.doi.org/10.1109/TPAMI.2007.70847

A. Bosch, A. Zisserman and X. Muoz, "Scene classification using a hybrid generative/discriminative approach", Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 30, no. 4, pp. 712-727, 2008 http://dx.doi.org/10.1109/TPAMI.2007.70716

T. Kato: Database architecture for content-based image retrieval. Proc. SPIE 1662. Image Storage and Retrieval Systems, vol. 1662, pp. 112-123, 1992 http://dx.doi.org/10.1117/12.58497

T. Dharani and I. Aroquiaraj: A survey on content based image retrieval. Pattern Recognition, Informatics and Mobile Engineering (PRIME), 2013 International Conference, pp. 485-490 http://dx.doi.org/10.1109/ICPRIME.2013.6496719

J. Vogel and B. Schiele, "Semantic modeling of natural scenes for content-based image retrieval", International Journal of Computer Vision, vol. 72, no. 2, pp. 133-157, 2007 http://dx.doi.org/10.1007/s11263-006-8614-1

K. Fukunaga, Introduction to Statistical Pattern Recognition, 1990, Academic Press Professional, Inc.


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