It is difficult to obtain images only we want on the web. Because, enormous data exist in the web. A present detection system of images are keyword detection which is added the name of keyword for images. Therefore, it is very important and difficult to add the keyword for images. In this paper, keywords in the image are analized by using the factor analysis and the sandglass-type neural network (SNN) for image searching. As images preprocessing, objective images are segmented by the maximin-distance algorithm. Small regions are integrated into a near region. Thus, objective images are segmented into some region. After this images preprocessing, keywords in images are analyzed by using factor analysis and a sandglass-type neural network (SNN) for image searching in this paper. Images data are corresponded to 2-dimensional data by using these two methods. 2-dimensional data are plotted on a graph. Images are recognized by using this graph.
CITATION STYLE
Ito, S., Mitsukura, Y., Fukumi, M., Akamatsu, N., & Omatu, S. (2003). The image recognition system by using the FA and SNN. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2773 PART 1, pp. 578–584). Springer Verlag. https://doi.org/10.1007/978-3-540-45224-9_79
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