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This paper presents a symbolic pattern analysis method for robust feature extraction from sidescan sonar images that are generated from autonomous underwater vehicles (AUVs). The proposed data-driven algorithm, built upon the concepts of symbolic dynamics and automata theory, is used for detection of mines and mine-like objects in the undersea environment. This real-time algorithm is based on symbolization...
This paper presents an efficient human recognition system based on vein patterns from the palma dorsa. A new absorption-based technique has been proposed to collect good quality images with the help of a low cost camera and light source. The system automatically detects the region of interest from the image and does the necessary preprocessing to extract features. Euclidean Distance based technique...
This paper presents symbolic pattern analysis of sidescan sonar images for detection of mines and mine-like objects in the underwater environment. For robust feature extraction, sonar images are symbolized by partitioning the data sets based on the information generated from the ground truth. A binary classifier is constructed for identification of detected objects into mine-like and non-mine-like...
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