This paper presents work done for oil spill detection along coastal waters. Consumers are primarily interested in automatic detection of oil spills. The main objective of this study is to develop an automatic model fo...
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This paper presents work done for oil spill detection along coastal waters. Consumers are primarily interested in automatic detection of oil spills. The main objective of this study is to develop an automatic model for oil spill detection. This model includes texture analysis and two types of algorithms (Lee and Gamma). texture analysis, such as contrast analysis, was used to discriminate between oil and water. The Lee algorithm was used to determine the linearity of oil movements, while the Gamma algorithm was used to determine oil spill spreading. The results showed that texture analysis and Lee and Gamma algorithms can be good modules for automatic detection of oil spills by using SAR data. Such modules will be useful for rapid detection of oil spills and is illustrative for educational purposes.
In this paper, a texture based algorithm is developed for classifying color images. The images are filtered by a set of Gabor filters at different scales and orientations. The energy of the filtered images in each cha...
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ISBN:
(纸本)0819436674
In this paper, a texture based algorithm is developed for classifying color images. The images are filtered by a set of Gabor filters at different scales and orientations. The energy of the filtered images in each channel and between channels are computed and used for classification. The normalized RGB, xyY and HIQ color spaces are used to identify the best space for classifying the color images. The best representation of the textures are found to be using normalized RGB and HIQ space and chrominance values. A filter selection process using texture similarity is adopted. Unichannel and interchannel features are computed. A feature reduction process is applied before using a classifier. The algorithm is used to classify sets of textures from databases of color texture images and it gives good results. It is also applied to Landsat TM images. The 7 channels are used and the best channels for classification of the image are found to be R and G. The algorithm has been designed to use the appropriate Gabor filters based on texture transition characteristics within and between channels. The algorithm performs better than using only the gray scale values of the color images.
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