A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss func...
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Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detect...
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Fast robotic unloading of piled deformable box-like objects (e.g. box-like sacks), is undoubtedly of great importance to the industry. Existing systems although fast, can only deal with layered, neatly placed configur...
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This paper proposes an automatic recognition scheme for hand printed Bangla (an Indian script) numerals using neural network models. A Topology Adaptive Self Organizing Neural Network is first used to extract from a n...
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In this paper we deal with performance improvement of robust PCA algorithms by replacing regular subsampling of images by an irregular image pyramid adapted to the expected image content. The irregular pyramid is a st...
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In this paper we present an invisible spatial domain watermarking technique. The technique divides the image into n small blocks and the intensity of some of these blocks are modified depending on the key, which is a ...
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This paper deals with parallelization and implementation aspects of PDE based image processing models for large cluster environments with distributed memory. As an example we focus on nonlinear isotropic diffusion fil...
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In this paper we provide a cryptanalysis of the well known "Optimal Differential Energy Watermarking (DEW)" scheme. The DEW scheme divides the image into some disjoint regions (each region containing two sub...
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An advanced Optical Character recognition (OCR) system is equipped with the module of the page layout analyser. It separates textual zones from non-textual zones. It identifies textual blocks from multicolumn document...
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An advanced Optical Character recognition (OCR) system is equipped with the module of the page layout analyser. It separates textual zones from non-textual zones. It identifies textual blocks from multicolumn documents and groups them into homogenous regions in terms of geometric shape and spatial distribution. All existing OCR modules developed for various Indian scripts can handle text only single-column documents. In this paper, a page, layout analyser that uses typical common features present in most of the Indian scripts is introduced. A simple compatibility criterion that allows various degrees of homogeneity is defined. The page-analyser is robust in the sense that it can distinguish text regions from non-textual entities such as images, rulers, and noisy signals due to smudges and poor quality of the paper. Test results are shown in two most popular Indian Scripts, Devnagari (Hindi) and Bangla.
A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss func...
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