Search

The content based image search and retrieve systems are grounded on their images characteristics: the colour histogram, the colour binary set, the texture or granulation which are materialized into images representation models. The search and retrieval of a content based image implies comparisons between the images. This thing involves the use of a huge amount of resources and for a very long period of time. That is why the comparison takes place between the image representation models. The measuring of the similarity between the two images can be determined in the following ways: by calculating the Minkowski distance, the Hamming distance, the square distance, generaliyed measure Jaccard and corelation measure Pearson. The study was realized for a set of three images compose by a one interrogation endoscopical image and two target endoscopical images (one relevant image and one irrelevant image). They are compareted results for all methods of establishing image similitude using the images representation models in the RGB colour space and the HSV color space. [ABSTRACT FROM AUTHOR]

This is a comparative study for nerecursive algorithms content search in multimedia databases with endoscopic images are based three methods of deciding the similarities between the models of images: Minkowsky distance, generalized measure Jaccard and correlated measure Pearson. The performance of the search has been measured according to three parameters: reapel, precision and the quality of retrieval. The model of representing the images are the normalized color histogram. The color space of the images are RGB reduced to 125 and 256 colors and HSV reduced to 162 and 256 colors. The study was realized in a database containing 360 images grouped in 23 categories. The results are presented both in tables and graphs. [ABSTRACT FROM AUTHOR]