7/29/2023 0 Comments Bitmap graphics examples332≣35.Are you feeling a bit Pixelated? - Vector graphics vs Bitmaps! 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. Batko, MUFIN Multifeature Indexing Network/ Image Search, Project web site,, , Masaryk University, Czech Republic, 2008. Batko, "Similarity Search The Metric Space Approach", in Advances in Datábase Systems, Springer, 2006. Yahoo! Inc., "flickr from Yahoo! almost certainly the best online photo management and sharing application in the world", Commercial web site,, , 2011. Marschner, Fundamentais of Computer Graphics, A.K. Stockman, Computer Vision, Prentice Hall, 2001. Norvig, Artificial Intelligence A modern approach, Prentice Hall, 2003. Maimón, "Topdown induction of decision trees classifiers: a survey," in IEEE Transactions on Systems, Man, and Cybernetics, Part C 35, IEEE Press, 2005, pp. 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. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann, 1993. Quinlan, "Induction of Decision Trees," Machine Learning, Volume 1, pp. Peli, "Contrast in Complex Images", Journal of the Optical Society of America A: Optics, Image Science, and Vision, Volume 7 (10), pp. Mitchell, Machine Learning McGraw Hill, 1997. Hildreth, "Theory of edge detection", Proceedings of the Royal Society of London, Series B, Volume 207 (1167), pp. Luksová, Klasifikace bitmapovych obrázkü (Classification of Bitmap Images), Bachelor thesis, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic, 2010. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Communications of the ACM, ACM Press, 1972. Hughes, Computer Graphics: Principies and Practice in C, AddisonWesley Professional, 1995. Rabitti, "CoPhIR: a Test Collection for Content≫ased Image Retrieval," CoRR abs/0905.4627,, , ISTI CNR, 2009. 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). Key words: Image classification, attribute extraction, decision trees, learning. 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. A performed experimental evaluation with 5 classification classes showed that the proposed method has the accuracy of 75%≨5%. Extracted attributes are subsequently processed by a decision tree which has been trained in advance. ![]() 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. Examples of such naturally defined classes are images depicting buildings, landscape, artistic images, etc. The paper addresses the design of a method for automated classification of bitmap images into classes described by the user in natural language. ![]() Manuscript accepted for publication August 20, 2011. Automated Classification of Bitmap Images using Decision TreesĬharles University in Prague, Faculty of Mathematics and Physics, Department of Theoretical Computer Science and Mathematical Logic, Malostranské námestí 25, Praha, 118 00, Czech Republic, (* ** received June 20, 2011.
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