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Teymourpour A, Taghipour-Gorjikolaie M, Razavi S M. Search Space Reduction in Farsi Machine-printed Sub-words Recognition by using Biometric Minutia Features. Journal of Iranian Association of Electrical and Electronics Engineers 2022; 19 (2) :189-199
URL: http://jiaeee.com/article-1-1159-en.html
University of Birjand
Abstract:   (938 Views)
Due to the wide range of Persian (Farsi) machine-printed sub-words, finding a sub-word and consequently a word in a machine-printed text will be very time consuming. In this paper, a biometric minutia based method is presented, which significantly reduces the search space of Farsi sub-words. Therefore, the number of points and their coordinates of bifurcated and ending minutia points, which are two well-known features in the field of biometrics, have been used as features to reduce the search space in the form of a two-step method. In the first step, the minutia points are extracted from the sub-word image and categorized into four clusters that are close and similar as a viewpoint of the number of minutia points. Therefore, search space will be halved by this step. In the second step, by creating a repository of the distances between the first and the last end points for each sub-word in each cluster and matching the same distance of experimental image with the repository, the search space is significantly reduced. Obtained results show that the search space has been reduced from 12,700 sub-words to about 500 sub-keywords with an accuracy of approximately 90%.
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Type of Article: Research | Subject: Electronic
Received: 2020/07/23 | Accepted: 2021/09/7 | Published: 2022/06/24

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