DOI : https://doi.org/10.18517/ijaseit.6.6.1457

Detection on Straight Line Problem in Triangle Geometry Features for Digit Recognition

N. A. Arbain (1), M. S. Azmi (2), S. S. S. Ahmad (3), R. Nordin (4), M. Z. Mas'ud (5), M. A. Lateh (6)
(1) Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
(2) Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
(3) Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
(4) Centre for Languages and Human Development,Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal,76100 Melaka, Malaysia
(5) Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
(6) Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100 Melaka, Malaysia
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How to cite (IJASEIT) :
Arbain, N. A., et al. “Detection on Straight Line Problem in Triangle Geometry Features for Digit Recognition”. International Journal on Advanced Science, Engineering and Information Technology, vol. 6, no. 6, Dec. 2016, pp. 1019-25, doi:10.18517/ijaseit.6.6.1457.
Citation Format :
Geometric object especially triangle geometry has been widely used in digit recognition area. The triangle geometry properties have been implemented as the triangle features which are used to construct the triangle shape. Triangle is formed based on three points of triangle corner A, B and C. However, a problem occurs when three points of triangle corner were in parallel line. Thus, an algorithm has been proposed in order to solve the straight line problem. The Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) were used to measure based on the classification accuracy. Four datasets were used: HODA, IFCHDB, MNIST and BANGLA. The comparison results classification demonstrated the effectiveness of our proposed method.
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