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An automatic road extraction method was proposed based on level set and shape metric for sensing digital image. Level set approach is applied for segmenting sensing image. Second order moment is calculated and the road networks are extracted using prior information about geometric shape. Experimental results on real remote sensing images show that this method is efficient in extracting road networks.
This paper proposes an information hiding method based on block-segmentation strategy. The proposed scheme divides a grayscale image into several 4 times 4 blocks and further segment each block into four small blocks sized 2 times 2. Each small block chooses one reference point to be proceeded with outer embedding process. The chosen points then formed an inner block to be proceeded with inner embedding...
The cellular neural/nonlinear network (CNN) is a powerful tool for image and video signal processing, robotic and biological visions. The robust designs for CNN templates are important issue for the practical applications of the CNN. The fingerprint feature extraction (FFE) CNNs are two kinds of CNNs, which are able to extract the endings and bifurcations in patterns, two important features in a fingerprint...
While people cluster images in terms of semantics, computers can not do too much on this job due to the use of lower-level features, which is the common way to computer workers to deal with the image recognition. To measure the closeness between feature vectors, similarity metrics play a key role and they directly impact the clustering performance. This paper develops a framework of learning pseudo...
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