9786139999262 - Enhancement of Degraded Text Images & Performance Comparison: A Research work on quality Enhancement of Poor Degraded Images von Sinha, Vijay Kumar; Verma, Karun (9 Ergebnisse)

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Taschenbuch. Zustand: Neu. Enhancement of Degraded Text Images & Performance Comparison | A Research work on quality Enhancement of Poor Degraded Images | Vijay Kumar Sinha (u. a.) | Taschenbuch | 68 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139999262 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Text recognition from distorted or degraded images especially handwritten is a challenge in computing . The present research work on 'Enhancement Of Degraded Text Images & Performance Comparison', is an excellent effort to enhance the degraded text images caused by poor scanning, historical papers, and other causes. This study will propose a technique for the enhancement of such a degraded text document images to improve their display quality characteristics by using thresh hold values as well as a comparison of performance among them. Images believed to be representative of the same symbol which occurs in different positions over an image source are clustered together. Using the symbols within a particular cluster, an average character image outline for that cluster of symbols is derived and thereafter used to refine the matching of symbols within the cluster and to determine a final representative symbol for that cluster. Thus the partially visible or distorted text can be recognized. The work will definitely prove a helping hand to young researchers for developing new ideas and algorithms to resolve the practical problems of text image degradation and their recovery. 68 pp. Englisch.

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sinha Vijay KumarProf. Vijay Kumar Sinha received his Ph.D. from IKGPTU, Kapurthala in Computer Science & Engineering. He received M.Tech. degree from Lovely Professional University in CSE, M.Tech.(IT) from Punjabi University, Patia.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Text recognition from distorted or degraded images especially handwritten is a challenge in computing . The present research work on 'Enhancement Of Degraded Text Images & Performance Comparison', is an excellent effort to enhance the degraded text images caused by poor scanning, historical papers, and other causes. This study will propose a technique for the enhancement of such a degraded text document images to improve their display quality characteristics by using thresh hold values as well as a comparison of performance among them. Images believed to be representative of the same symbol which occurs in different positions over an image source are clustered together. Using the symbols within a particular cluster, an average character image outline for that cluster of symbols is derived and thereafter used to refine the matching of symbols within the cluster and to determine a final representative symbol for that cluster. Thus the partially visible or distorted text can be recognized. The work will definitely prove a helping hand to young researchers for developing new ideas and algorithms to resolve the practical problems of text image degradation and their recovery.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Text recognition from distorted or degraded images especially handwritten is a challenge in computing . The present research work on 'Enhancement Of Degraded Text Images & Performance Comparison', is an excellent effort to enhance the degraded text images caused by poor scanning, historical papers, and other causes. This study will propose a technique for the enhancement of such a degraded text document images to improve their display quality characteristics by using thresh hold values as well as a comparison of performance among them. Images believed to be representative of the same symbol which occurs in different positions over an image source are clustered together. Using the symbols within a particular cluster, an average character image outline for that cluster of symbols is derived and thereafter used to refine the matching of symbols within the cluster and to determine a final representative symbol for that cluster. Thus the partially visible or distorted text can be recognized. The work will definitely prove a helping hand to young researchers for developing new ideas and algorithms to resolve the practical problems of text image degradation and their recovery.