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Morphological Image Enhancement and Segmentation


Affiliations
1 Department of Information and Technology, Cauvery College for Women, Trichy, India
2 Department of Computer Science and Engineering, JJ College of Engineering and Technology, Trichy, India
     

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In this paper, some morphological transformations are used to detect the background in images characterized by poor lighting. Lately, contrast image enhancement has been carried out by the application of two operators based on the Weber’s law notion. The first operator employs information from block analysis, while the second transformation utilizes the opening by reconstruction, which is employed to define the multi background notion. The objective of contrast operators consists in normalizing the grey level of he input image with the purpose of avoiding abrupt changes in intensity among the different regions. Finally, the performance of the proposed operators is illustrated through the processing of images with different backgrounds, the majority of them with poor lighting conditions.

Keywords

Connected Transformations, Contrast Mappings, Morphological Contrast Measure.
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  • Morphological Image Enhancement and Segmentation

Abstract Views: 128  |  PDF Views: 2

Authors

K. Reka
Department of Information and Technology, Cauvery College for Women, Trichy, India
G. Raja
Department of Computer Science and Engineering, JJ College of Engineering and Technology, Trichy, India

Abstract


In this paper, some morphological transformations are used to detect the background in images characterized by poor lighting. Lately, contrast image enhancement has been carried out by the application of two operators based on the Weber’s law notion. The first operator employs information from block analysis, while the second transformation utilizes the opening by reconstruction, which is employed to define the multi background notion. The objective of contrast operators consists in normalizing the grey level of he input image with the purpose of avoiding abrupt changes in intensity among the different regions. Finally, the performance of the proposed operators is illustrated through the processing of images with different backgrounds, the majority of them with poor lighting conditions.

Keywords


Connected Transformations, Contrast Mappings, Morphological Contrast Measure.