Contrast variables and uneven illumination are considered one of the most challenging tasks in the image processing field. The bad contrast images commonly caused by occlusion, pose, illumination which is highly nonlinear. Thus, the segmentation process will be extremely complex and difficult. In this work, contrast and luminosity correction technique will be developed based on statistical formulation. The background pixels will be used in order to estimate the normalize background using the mean and standard deviation. This experimented was tested with a few badly illuminated images and document images which involve illumination and contrast problem. The result will be evaluated and analysis properly. The main impact of this study is to eliminate the illumination and normalize the contrast variation. In conclusions, the implementation of the proposed method produces an effective and efficient result for background correction.
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Contrast variables and uneven illumination are considered one of the most challenging tasks in the image processing field. The bad contrast images commonly caused by occlusion, pose, illumination which is highly nonlinear. Thus, the segmentation process will be extremely complex and difficult. In this work, contrast and luminosity correction technique will be developed based on statistical formulation. The background pixels will be used in order to estimate the normalize background using the mean and standard deviation. This experimented was tested with a few badly illuminated images and document images which involve illumination and contrast problem. The result will be evaluated and analysis properly. The main impact of this study is to eliminate the illumination and normalize the contrast variation. In conclusions, the implementation of the proposed method produces an effective and efficient result for background correction.
Degree in Biomedical Electronic Engineering (2013) and PhD in Mechatronic Engineering (2017), Fast Track Program at University Malaysia Perlis, Malaysia. Registered on Board Engineer Malaysia (BEM) 2014.Published more than 10 academic articles.Now working as a senior lecturer at University Malaysia Perlis, Malaysia.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Contrast variables and uneven illumination are considered one of the most challenging tasks in the image processing field. The bad contrast images commonly caused by occlusion, pose, illumination which is highly nonlinear. Thus, the segmentation process will be extremely complex and difficult. In this work, contrast and luminosity correction technique will be developed based on statistical formulation. The background pixels will be used in order to estimate the normalize background using the mean and standard deviation. This experimented was tested with a few badly illuminated images and document images which involve illumination and contrast problem. The result will be evaluated and analysis properly. The main impact of this study is to eliminate the illumination and normalize the contrast variation. In conclusions, the implementation of the proposed method produces an effective and efficient result for background correction. 60 pp. Englisch. N° de réf. du vendeur 9783330064058
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Contrast variables and uneven illumination are considered one of the most challenging tasks in the image processing field. The bad contrast images commonly caused by occlusion, pose, illumination which is highly nonlinear. Thus, the segmentation process will be extremely complex and difficult. In this work, contrast and luminosity correction technique will be developed based on statistical formulation. The background pixels will be used in order to estimate the normalize background using the mean and standard deviation. This experimented was tested with a few badly illuminated images and document images which involve illumination and contrast problem. The result will be evaluated and analysis properly. The main impact of this study is to eliminate the illumination and normalize the contrast variation. In conclusions, the implementation of the proposed method produces an effective and efficient result for background correction. N° de réf. du vendeur 9783330064058
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mustafa Wan AzaniDegree in Biomedical Electronic Engineering (2013) and PhD in Mechatronic Engineering (2017), Fast Track Program at University Malaysia Perlis, Malaysia. Registered on Board Engineer Malaysia (BEM) 2014.Published mor. N° de réf. du vendeur 151235720
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Contrast variables and uneven illumination are considered one of the most challenging tasks in the image processing field. The bad contrast images commonly caused by occlusion, pose, illumination which is highly nonlinear. Thus, the segmentation process will be extremely complex and difficult. In this work, contrast and luminosity correction technique will be developed based on statistical formulation. The background pixels will be used in order to estimate the normalize background using the mean and standard deviation. This experimented was tested with a few badly illuminated images and document images which involve illumination and contrast problem. The result will be evaluated and analysis properly. The main impact of this study is to eliminate the illumination and normalize the contrast variation. In conclusions, the implementation of the proposed method produces an effective and efficient result for background correction.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. N° de réf. du vendeur 9783330064058
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Image Enhancement Based on Indirect Techniques | Wan Azani Mustafa (u. a.) | Taschenbuch | 60 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330064058 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 108873856
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