This paper presents an approach to extract curved text lines from Arabic handwritten documents, based on the perception mechanisms involved in the human reading process. Our approach is based on multi-agent systems to detect and group connected components that belong to the same line. This proposed system makes use of information about features and arrangement of those components. Experimental results on a data-set of Arabic handwritten documents show that this approach is a promising solution for extracting handwritten curved text lines.

This study presents a new approach for processing of Arabic handwritten documents based on the extraction of characteristics and mechanisms involved in the process of human visual perception. The architecture which has been developed is based on the concept of multi-agent systems, allowing the integration of different stages of character recognition process in a cooperative way. This is illustrated using as example the prepossessing of binary noisy document. Therefore, a method was proposed, in order to distinguish between text and non-text components, using a new geometric primitives extracted from the analysis of the characteristics of Arabic script. Results show pixel-level precision and recall respectively of 98% and 93% for noise removal. This proves the effectiveness of the proposed approach in processing degraded documents and, consequently, improving the recognition performance.

In this paper, the notion of 2-absorbing δ-primary Γ-ideal of Γ-ring is introduced which unify 2-absorbing Γ-ideal and 2-absorbing δ-primary Γ-ideal , and several properties are investigated. Here δ is a mapping that assigns to each Γ-ideal J a Γ-ideal δ(J) of the same Γ-ring such that:(1) (∀I ∈ J(M ))(I ⊆ δ(I)),(2) (∀I, J ∈ J(M )))(I ⊆ J ⇒ δ(I) ⊆ δ(J)), where J(M ) is the set of Γ-ideal of Γ-ring M .

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