Swarm-Based Feature Selection for Handwriting Identification

Abdl, Khaled Mohammed bin; Hashim, Siti Zaiton Mohd

doi:10.3844/jcssp.2010.80.86

Cited by 7 publications

(5 citation statements)

References 19 publications

(20 reference statements)

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“…The research in Roman handwriting [25], [26], the researchers have used different methods to obtain the data input for their research. Moreover, there are also two types of datasets that were used in [25].…”

Section: Roman Paleographymentioning

confidence: 99%

“…Whilst, in the IAM dataset, it consists of English handwriting that has been written by 657 subjects using different pens [28]. In 2010, the researchers [26] had also used the IAM data as the data input in the research. 956 words of the offline IAM dataset have been trained whereas each word is represented by 29 statistical features.…”

Section: Roman Paleographymentioning

confidence: 99%

“…956 words of the offline IAM dataset have been trained whereas each word is represented by 29 statistical features. [26] has presented the swarm intelligence as a features weighting mechanism to distinguish between a feature that has high importance and low importance in the identification process. Then, the weights are acquired from swarm experiments which are then used to alter the feature scores.…”

Section: Roman Paleographymentioning

confidence: 99%

See 2 more Smart Citations

State of the Art in Digital Paleography

Arbain¹

2019

IJATCSE

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Digital paleography is an approach used to assist paleographers in deciding the origin of manuscripts. This is done by recording types of writings present in old manuscripts. It uses digital representation of book hands as a tool to support paleographical analyses by human experts. There are six types of manuscripts selected which are Arabic, Chinese, Jawi, Indian, Latin and Roman. These types of manuscripts are discussed through their current contribution in the digital paleography field. The main purpose of this paper is to discuss the current work on digital paleography for selected types of manuscripts. Thus, we identified the approaches and methods used to define the types of handwritings in old manuscripts

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Section: Roman Paleographymentioning

confidence: 99%

Section: Roman Paleographymentioning

confidence: 99%

Section: Roman Paleographymentioning

confidence: 99%

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State of the Art in Digital Paleography

Arbain¹

2019

IJATCSE

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“…Recently, different approaches for writer identification have been proposed. These approaches are generally categorized as off-line, where only a scanned image of the handwriting is available and Online (Al-Omari et al, 2009;Hashim and Abdl, 2010), where temporal and spatial information about the writing is available. In this context, (Al-Omari et al (2009), presents a method for identification of writer, who describes an off-line approach based on texture analysis.…”

Section: Introductionmentioning

confidence: 99%

A Novel Fractal Approach for Persian/Arabic Identification based on Handwriting Recognition

Farshchi¹

2011

Journal of Computer Science

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Problem statement: In recent years, fractal and multi-fractal analysis have been widely applied in many domains, especially in the field of image processing. In this study we presented a novel method for Persian and Arabic text-dependent writer identification based on fractal and multifractal features. Approach: From the images of Persian or Arabic words, we calculated their fractal dimensions by using the "Box-counting" method and then we calculated their multi-fractal dimensions by using the method of Diffusion Limited Aggregates (DLA). Results: To evaluate our method, we used 50 writers of the PERSIANDB database, each writer wrote 288 words (24 words repeated 12 times) with 2/3 of words are used for the learning phase and the rest is used for the identification. Conclusion:The results obtained by using k nearest neighbor classifier, demonstrated the effectiveness of our proposed method.

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“…The notion of stigmergy means the indirect communication of individuals through modifying their environment. Several algorithms which are based on ant colony problems were introduced in recent years to solve different problems, e.g., optimization problems, image segmentation (Ouadfel and Batouche, 2007;Ibrahim et al, 2005;Hashim and Abdl, 2010).…”

Section: Introductionmentioning

confidence: 99%

Enhanced Clustering Techniques for Hyper Network Planning using Minimum Spanning Trees and Ant-Colony Algorithm

Ibrahim¹

2011

Journal of Computer Science

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Problem statement:The process of network planning is divided into two sub steps. The first step is determining the location of the Multi Service Access Node (MSAN). The second step is the construction of subscriber network lines from MSAN to subscribers to satisfy optimization criteria and design constraints. Due to the complexity of this process artificial intelligence and clustering techniques have been successfully deployed to solve many problems. The problems of the locations of MSAN, the cabling layout and the computation of optimum cable network layouts have been addressed in this study. The proposed algorithm, Clustering density-Based Spatial of Applications with Noise original, minimal Spanning tree and modified Ant-Colony-Based algorithm (CBSCAN-SP-ANT), used two clustering algorithms which are density-based and agglomerative clustering algorithm using distances which are shortest paths distance and satisfying the network constraints. This algorithm used wire and wireless technology to serve the subscribers demand and place the switches in a real optimal place. Approach: The density-based Spatial Clustering of Applications with Noise original (DBSCAN) algorithm has been modified and a new algorithm (NetPlan algorithm) has been proposed by the author in a recent work to solve the first step in the problem of network planning. In the present study, the NetPlan algorithm is modified by introduce the modified Ant-Colony-Based algorithm to find the optimal path between any node and the corresponding MSAN node in the first step of network planning process to determine nodes belonging to each cluster. The second step, in the process of network planning, is also introduced in the present study. For each cluster, the optimal cabling layout from each MSAN to the subscriber premises is determining by introduce the Prime algorithm which construct minimal spanning tree. Results: Experimental results and analysis indicate that the CBSCAN-SP-ANT algorithm was effective, leads to minimum costs for network construction and make the best grade of service. Conclusion: Using mobile network to serve the area with low density is decreasing the cost of design the fixed wire network. Also, using the modified ANT algorithm and minimum spanning tree, are helping to construct the cable layout from each MSAN to subscribers when the network is complicated and the number of intersections and streets are large.

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Swarm-Based Feature Selection for Handwriting Identification

Cited by 7 publications

References 19 publications

State of the Art in Digital Paleography

State of the Art in Digital Paleography

A Novel Fractal Approach for Persian/Arabic Identification based on Handwriting Recognition

Enhanced Clustering Techniques for Hyper Network Planning using Minimum Spanning Trees and Ant-Colony Algorithm

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