Open AccessCAViz, an Interactive Graphical Tool for Image Mining
Author(s) -
Nguyen-Khang Pham,
Annie Morin,
Patrick Gros
Publication year - 2008
Publication title -
cit. journal of computing and information technology/journal of computing and information technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.169
H-Index - 27
eISSN - 1846-3908
pISSN - 1330-1136
DOI - 10.2498/cit.1001397
Subject(s) - computer science , contingency table , scale invariant feature transform , row , table (database) , artificial intelligence , image (mathematics) , feature (linguistics) , simple (philosophy) , pattern recognition (psychology) , invariant (physics) , structuring , information retrieval , data mining , natural language processing , machine learning , mathematics , database , mathematical physics , epistemology , finance , linguistics , philosophy , economics
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