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Recognizing Text Objects within Images By Uses Fractal Dimension
Author(s) -
Omar A. Najim,
Eklass A. Sultan,
Hanaa Mahmood
Publication year - 2009
Publication title -
mağallaẗ al-tarbiyaẗ wa-al-ʻilm
Language(s) - English
Resource type - Journals
eISSN - 2664-2530
pISSN - 1812-125X
DOI - 10.33899/edusj.2009.57706
Subject(s) - fractal dimension , box counting , fractal , artificial intelligence , pattern recognition (psychology) , fractal analysis , image (mathematics) , pixel , dimension (graph theory) , feature (linguistics) , grayscale , fractal transform , computer vision , computer science , mathematics , image processing , mathematical analysis , combinatorics , image compression , linguistics , philosophy
This paper proposes a new algorithm for recognizing text object images by using fractal geometry. The fractal dimension was used as a main feature for recognizing text objects within images. Box-counting method was used to estimate the fractal dimension for image contents. In order to determine a threshold value for the textual objects within image, the fractal dimension was computed for a number of gray scale textual images. The fractal number of each pixel was calculated, then the mean value of all these fractal values were computed. The threshold value was used in recognizing and retrieving the textual objects within image. Recognizing Text Objects within Images By Uses Fractal Dimension. 168 This algorithm was applied on 75 image samples, 25 image samples were used in training phase, the threshold value was determined throughout this phase; whereas 50 image samples were used in testing the algorithm. The proposed algorithm has performed extremely well with recognition rates 91.5% which is considered good performance. It is a promising technique for optical character recognition system.

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