JACIII Vol.13 No.5 pp. 573-580
doi: 10.20965/jaciii.2009.p0573


Object Categorization Using Biologically Inspired Nodemaps and the HITEC Categorization System

Adam Csapo, Barna Resko, Domonkos Tikk, and Peter Baranyi

Budapest Univ. of Technology and Economics, H-1111, Budapest, Muegyetem Rkp. 3-9, Hungary
Computer and Automation Research Institute, Hungarian Academy of Sciences, H-1111, Budapest, Kende u. 13-17, Hungary

January 10, 2009
March 7, 2009
September 20, 2009
cognitive informatics, image categorization, Visual Feature Array, HITEC

The computerized modeling of cognitive visual information has been a research field of great interest in the past several decades. The research field is interesting not only from a biological perspective, but also from an engineering point of view when systems are developed that aim to achieve similar goals as biological cognitive systems. This paper briefly describes a general framework for the extraction and systematic storage of low-level visual features, and demonstrates its applicability in image categorization using a linear categorization algorithm originally developed for the characterization of text documents. The performance of the algorithm together with the newly developed feature array was evaluated using the Caltech 101 database. Extremely high (95% and higher) success rates were achieved when distinguishing between pairs of categories using independent test images. Efforts were made to scale up the number of categories using a hierarchical, branch-and-bound decision tree, with limited success.

Cite this article as:
A. Csapo, B. Resko, D. Tikk, and P. Baranyi, “Object Categorization Using Biologically Inspired Nodemaps and the HITEC Categorization System,” J. Adv. Comput. Intell. Intell. Inform., Vol.13, No.5, pp. 573-580, 2009.
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Last updated on Dec. 02, 2022