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Machine Learning Classification Algorithms to Recognize Chart Types in Portable Document Format (PDF) Files
Author(s) -
V. Karthikeyani,
S. Nagarajan
Publication year - 2012
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/4789-6997
Subject(s) - computer science , chart , artificial intelligence , machine learning , information retrieval , algorithm , natural language processing , statistics , mathematics
recognition system from PDF files is a relatively young research field where techniques and algorithms are proposed to identify type of charts and interpret them. This paper focus on recognition of chart type that is a part of PDF document using texture features and classification algorithm. Eleven types of texture features and three classifiers, namely, Multilayer perceptron, support vector machine and K nearest neighbour, are used. Performance analysis of the proposed chart type recognition systems show that texture features for chart type recognition has promising future and produces best result while using KNN and SVM algorithm.

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