Técnicas de clusterização baseadas em características de cor para a consulta em bancos de dados de imagens

Abstract

The current technologies for acquisition, storage and transmission of digital data, generate large amounts of data. This quantitative increase is directly proportional to the expansion of multimedia databases, where the bases are part of images. Factors contributing to this expansion is the generation of data access and multimedia, which are frequently used by the population through the media today. Thus, we find a clear need exists for automated systems, capable of dealing with the storage and retrieval of data in a time acceptable to the current standards. To this end, systems are designed for content retrieval of images, where the content is described through its low-level visual features such as shape, texture and color. To have such a system is considered ideal, it must be efficient and effective. The effectiveness will result from the way the information was obtained as a low level of images, considering different conditions of focus, lighting and occlusion. The efficiency is a consequence of the results obtained using the organization of information extracted. The methods of grouping are in one of the useful techniques to reduce the computational complexity of these systems, reducing the computational complexity of the methods implemented, but without losing the representation of information extracted. This work proposes a method for retrieval of images based on content, using appropriate techniques of clustering, a technique for detecting edges and a method to normalize the images in the aspect of enlightenment, to get through it the image descriptors that are robust and can be applied efficiently in a retrieval system for images by content - CBIR (Content Based Image Retrieval).