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Persian Document Recognition Using Novel Persian Word Indexing Technique and Fused Shape Matching Method AISRG
Hamed Habibi Aghdam
Conference : ICDIP , Singapore, Febuary - 2010
Abstract - There are two main techniques for recognizing Persian documents. Segmentation technique has been studied completely and several applicable methods were proposed using this technique. In contrast shape matching techniques is still active research area and few methods proposed for this technique. In fact they are complementary techniques which fusion of them produces a powerful tool for recognizing Persian documents. In this paper we study the major segmentation methods and analyze their functionality from different views. Then, we show how shape matching method works and propose a novel Persian word indexing technique. Finally we describe how these two methods can be fused and test several aspects of the proposed method.
   
A Simulated Annealing Approach for Maximizing the Accrued Utility of an Isochronal Soft Real-Time System AISRG
Ali Asghar Pourhaji Kazem, Neda Dadashkhani, Mehdi Kargahi, Hamed Habibi Aghdam
Conference : ICECS , Dubai , UAE , December - 2009
   
Novel Framework for Selecting the Optimal Feature Vector from Large Feature Spaces AISRG
Hamed Habibi Aghdam - Saeid Payvar
Journal : Accepted in Journal of Communication and Computer, USA, August-2009
   
Novel Framework for Selecting the Optimal Feature Vector from Large Feature Spaces AISRG
Hamed Habibi Aghdam - Saeid Payvar
Abstract - There are several feature extracting techniques which can produce a large feature space for a given image. It is clear that only small numbers of these features are appropriate to classify the objects. But selecting an appropriate feature vector from the large feature space is a hard optimization problem. In this paper we address this problem using the well known optimization technique called Simulated Annealing. Also we show that how this framework can be used to design the optimal 2D rectangular filter banks for Printed Persian and English numerals classification, Printed English letters classification, Eye, Lip and Face detection problems.
Conference : ICIAR 2009 - Halifax, Canada, July-2009
   
A Novel Corner Detector with Integrated Corner Angle Computation AISRG
Hamed Habibi Aghdam - Ali Asghar Pourhaji Kazem
Abstract - Corner detection is widely used in image processing and machine vision. Hence, different corner detectors are proposed. But the performance of such corner detectors is sensitive to round effect and curve shape of the edges. In this paper we propose a novel corner detector that either over come corner detection problems and produces some information about detected corners that is very useful in segmentation and object recognition.
Conference : IWSSIP 2008 - Bratislava, Slovak Republic, July-2008
   
A Modified Simulated Annealing Algorithm for Static Task Scheduling in Grid Computing AISRG
Hamed Habibi Aghdam - Ali Asghar Pourhaji Kazem - Amir Masoud Rahmani
Abstract - Grid Computing aims to allow unified access to data, computing power, sensors and other resources through a single virtual laboratory. The development or adaptation of applications for Grid environments is being challenged by the need of scheduling a large number of tasks and resources efficiently. The general problem of optimally mapping tasks to machines in a heterogeneous computing suite has been shown to be NP-complete. In this paper we propose a modified simulated annealing algorithm for scheduling independent tasks in Grid environment. Experimental results show that our proposed algorithm improves the performance of static instances compared to the results of other algorithms reported in the literature.
Conference : ICCSIT 2008 - Singapore, September-2008
   
Practical Framework for Extracting Data from Matrix Based Documents AISRG
Hamed Habibi Aghdam
Abstract - One of the major applications of the image processing is extracting data from digitally scanned documents. But in some cases such as matrix based documents, we cannot use any OCR techniques for this purpose. In this paper we propose a practical framework for developing an autonomous data extraction and classification system for matrix based documents. Considering that this is a practical paper, we do not introduce any new methods but practical results of implemented data extraction system from the special digitally scanned documents.
Conference : IVCNZ 2008 - New Zealand, November-2008
   
 

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