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This paper presents a novel local threshold segmentation algorithm for digital images incorporating shape information. In image segmentation, most of local threshold algorithms are only based on intensity analysis. In many applications where an image contains objects with a similar shape, besides the intensity information, prior known shape attributes could be exploited to improve the segmentation...
In this paper, a novel technique is proposed to identify computer graphics by employing second-order statistics to capture the significant statistical difference between computer graphics and photographic images. Due to the wide availability of JPEG images, a JPEG 2-D array formed from the magnitudes of quantized block DCT coefficients is deemed a feasible input; however, a difference JPEG 2-D array...
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning algorithms that induce a mapping from pixel features to individual pixel labels. In contrast we propose to first extract features from both images and labels. Subsequently we induce a mapping from pixel features to label features...
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