CAViz, an Interactive Graphical Tool for Image Mining

Nguyen-Khang Pham, Annie Morin, Patrick Gros

Abstract


We propose an interactive graphical tool, CAViz, which allows us to display and to extract knowledge from the results of a Correspondence Analysis CA on images. CA is a descriptive technique designed to analyze simple two-way and multi-way tables containing some measure of correspondence between the rows and columns. CA is very often used in Textual Data Analysis (TDA) where the contingency table crosses words and documents. In image mining, the first step is to define “visual” words in images (similar to words in texts). These words are constructed from local descriptors (SIFT, Scale Invariant Feature Transform) in images. Our tool CAViz is interactive, and it helps the user interpretating the results and the graphs of CA. An application to the Caltech4 base [15] illustrates the interest of CAViz in image mining.

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DOI: https://doi.org/10.2498/cit.1001397

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