An Efficient Method for Urdu Language Text Search in Image Based Urdu Text
This paper describes an efficient method for Urdu text search in computer generated and handwritten scanned images. An efficient text search technology is necessary because of increasing handled document every day. This method is unique and simple in the sense that no features are extracted. The proposed method is script independent. The input image is directly matched with a set of prototype characters representing each possible class. The distance between each input image and each prototype character is computed, and the character is assigned to the class of the prototype giving the best match. Experimental results show 100 % accuracy for 4, 5-character ligatures, 87 % for 3-character ligature and 78 % for 2-character ligatures.
Keywords: Template matching, correlation analysis, optical character recognition, source image, template image.
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ABOUT THE AUTHORS
Khalil Khan
Khalil Khan is pursuing his M.Sc. computer System engineering from University of Engineering & Technology, Peshawar, Pakistan. He has completed his B.Sc. Electrical engineering from the same university. He worked as switching engineer at ZTE pvt. ltd. in Optical fiber and Switching department for two and half year. He also worked as a lecturer in Electrical engineering department, University of Lahore, Islamabad campus. Currently he is working as a Principal Dir College of Science & Technology. His research interest areas are image processing, computer vision, machine learning and pattern recognition.
Muhammad Sidique
Muhammad Sidique did B.Sc. Computer System engineering from University of engineering & Technology, Peshawar, Pakistan. He is also pursuing his M.Sc. computer System engineering from University of Engineering & Technology, Peshawar. He is working as a System Engineer in Ghulam Ishaq Khan Institute of Science & Technology, Topi, Pakistan
Muhammad Aamir
Muhammad Aamir completed his B.E and M.SC from UET peshawar. Currently, he is working as an Assistant Professor at Sarhad University of Science and IT, Peshawar, Pakistan.
Rehan Ullah
Dr. Rehanullah graduated from University of Engineering and Technology Peshawar, with a BSc degree (Computer Engineering) in 2004 and MSc (Information Systems) in 2006. He obtained PhD degree (Computer Science) in 2011 from Vienna University of Technology, Austria. He is currently an Assistant Professor at Sarhad University of Science and Technology, Peshawar. His research interests include color interpretation, segmentation and object recognition.
Khalil Khan
Khalil Khan is pursuing his M.Sc. computer System engineering from University of Engineering & Technology, Peshawar, Pakistan. He has completed his B.Sc. Electrical engineering from the same university. He worked as switching engineer at ZTE pvt. ltd. in Optical fiber and Switching department for two and half year. He also worked as a lecturer in Electrical engineering department, University of Lahore, Islamabad campus. Currently he is working as a Principal Dir College of Science & Technology. His research interest areas are image processing, computer vision, machine learning and pattern recognition.
Muhammad Sidique
Muhammad Sidique did B.Sc. Computer System engineering from University of engineering & Technology, Peshawar, Pakistan. He is also pursuing his M.Sc. computer System engineering from University of Engineering & Technology, Peshawar. He is working as a System Engineer in Ghulam Ishaq Khan Institute of Science & Technology, Topi, Pakistan
Muhammad Aamir
Muhammad Aamir completed his B.E and M.SC from UET peshawar. Currently, he is working as an Assistant Professor at Sarhad University of Science and IT, Peshawar, Pakistan.
Rehan Ullah
Dr. Rehanullah graduated from University of Engineering and Technology Peshawar, with a BSc degree (Computer Engineering) in 2004 and MSc (Information Systems) in 2006. He obtained PhD degree (Computer Science) in 2011 from Vienna University of Technology, Austria. He is currently an Assistant Professor at Sarhad University of Science and Technology, Peshawar. His research interests include color interpretation, segmentation and object recognition.
