A Multi-Agent Approach to Segment Arabic Handwritten Text Lines

Mohsine Elkhayati, Youssfi Elkettani and Mohammed Mourchid
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Mohsine Elkhayati: University Ibn Tofail, Morocco
Youssfi Elkettani: University Ibn Tofail, Morocco
Mohammed Mourchid: University Ibn Tofail, Morocco

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2020, vol. 14, issue 4, 82-100

Abstract: In text line segmentation, there are three classes of methods: either by sorting physical units such as pixels or connected components (CC) constituting a line or by searching for the baseline of each word and grouping together those who participate in the same line. The third class analyzes the separation locations between the lines. After an overview of lines segmentation approaches, the authors introduced a new method emphasizing its simplicity, speed, and originality. The proposed approach detects the starting components of the lines in the first step. In the second step, it defines a number of agents that start the segmentation process from their starting points between the starting components of lines. Each agent aims to reach the left edge of the document through the correct path. The algorithm used by the agents is based on the morphological process, characteristics of the Arabic manuscript and a communication system. The experimental results on an Arabic dataset show that this approach is an effective solution for the segmentation of lines from different Arabic manuscripts.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jcini0:v:14:y:2020:i:4:p:82-100

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