versão On-line ISSN 1870-9044
Polibits no.44 México Jul./Dez. 2011
Automated Classification of Bitmap Images using Decision Trees
Pavel Surynek* and Ivana Luksová**
Charles University in Prague, Faculty of Mathematics and Physics, Department of Theoretical Computer Science and Mathematical Logic, Malostranské námestí 25, Praha, 118 00, Czech Republic, (*firstname.lastname@example.org, **email@example.com).
Manuscript received June 20, 2011.
Manuscript accepted for publication August 20, 2011.
The paper addresses the design of a method for automated classification of bitmap images into classes described by the user in natural language. Examples of such naturally defined classes are images depicting buildings, landscape, artistic images, etc. The proposed classification method is based on the extraction of suitable attributes from a bitmap image such as contrast, histogram, the occurrence of straight lines, etc. Extracted attributes are subsequently processed by a decision tree which has been trained in advance. A performed experimental evaluation with 5 classification classes showed that the proposed method has the accuracy of 75%85%. The design of the method is general enough to allow the extension of the set of classification classes as well as the number of extracted attributes to increase the accuracy of classification.
Key words: Image classification, attribute extraction, decision trees, learning.
We would like to gratefully thank the Czech Science Foundation and The Ministry of Education, Youth and Sports, Czech Republic for the financial support of this work (contracts 201/09/P318 and MSM 0021620838 respectively).
 P. Bolettieri, A. Esuli, F. Falchi, C. Lucchese, R. Perego, T. Piccioli, and F. Rabitti, "CoPhIR: a Test Collection for ContentBased Image Retrieval," CoRR abs/0905.4627, http://cophir.isti.cnr.it/, [accessed June, 2011], ISTI CNR, 2009. [ Links ]
 J. D. Foley, A. van Dam, S. K. Feiner, and J. F. Hughes, Computer Graphics: Principies and Practice in C, AddisonWesley Professional, 1995. [ Links ]
 R. O. Duda and P. E. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Communications of the ACM, ACM Press, 1972. [ Links ]
 I. Luksová, Klasifikace bitmapovych obrázkü (Classification of Bitmap Images), Bachelor thesis, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic, 2010. [ Links ]
 D. Marr and E. C. Hildreth, "Theory of edge detection", Proceedings of the Royal Society of London, Series B, Volume 207 (1167), pp. 187217, The Royal Society, 1980. [ Links ]
 T. M. Mitchell, Machine Learning McGraw Hill, 1997. [ Links ]
 E. Peli, "Contrast in Complex Images", Journal of the Optical Society of America A: Optics, Image Science, and Vision, Volume 7 (10), pp. 20322040, OSA, 1990. [ Links ]
 J. R. Quinlan, "Induction of Decision Trees," Machine Learning, Volume 1, pp. 81106, Springer, 1986. [ Links ]
 J. R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann, 1993. [ Links ]
 T. Rabbani and F. van den Heuvel, "Efficient Hough transform for automatic detection of cylinders in point clouds", in ISPRS Workshop Laser scanning 2005, Institute of Photogrammetry and Remote Sensing, 2005, pp. 6065. [ Links ]
 L. Rokach and O. Maimón, "Topdown induction of decision trees classifiers: a survey," in IEEE Transactions on Systems, Man, and Cybernetics, Part C 35, IEEE Press, 2005, pp. 476-487. [ Links ]
 S. Russel and P. Norvig, Artificial Intelligence A modern approach, Prentice Hall, 2003. [ Links ]
 L. G. Shapiro and G. C. Stockman, Computer Vision, Prentice Hall, 2001. [ Links ]
 P. Shirley, M. Ashikhmin, and S. Marschner, Fundamentais of Computer Graphics, A.K. Peters, 2009. [ Links ]
 Yahoo! Inc., "flickr from Yahoo! almost certainly the best online photo management and sharing application in the world", Commercial web site, http://www.flickr.com/, [accessed June, 2011], 2011. [ Links ]
 P. Zezula, G. Amato, V. Dohnal, and M. Batko, "Similarity Search The Metric Space Approach", in Advances in Datábase Systems, Springer, 2006. [ Links ]
 P. Zezula, G. Amato, V. Dohnal, and M. Batko, MUFIN Multifeature Indexing Network/ Image Search, Project web site, http://mufin.fi.muni.cz/imgsearch/, [accessed June, 2011], Masaryk University, Czech Republic, 2008. [ Links ]
 L. Zhai, S. Dong, and H. Ma, "Recent Methods and Applications on Image Edge Detection", in International Workshop on Education Technology and Training and International Workshop on GeoScience and Remóte Sensing, IEEE Press, 2008, pp. 332335. [ Links ]