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Segmentation of vessel structures in 3D volume data is of great interest for diagnosis and surgical planning. There are a number of methods that employ various intensity-based, textural, or geometric features for vessel extraction from 3D volume data. However, these methods are not successful in the low-contrast and inhomogeneous environments, especially in case of thinner blood vessels. In this study,...
This paper utilizes the characteristics of the Human Visual System (HVS) for obtaining better results in denoising color images corrupted by Gaussian noise. Implementation of the Contrast Sensitivity Function (CSF) of the HVS is done in each of the sub-bands in the wavelet domain. In this paper, an 11-weight Invariant Single Factor (ISF) system is proposed and implemented which outperforms the generally...
Detection and classification of vehicles are the most challenging tasks of a video-based intelligent transportation system. Traditional detection and classification methods are based on subtraction of estimated still backgrounds from a video to find out the moving objects. In general, these methods are computationally highly expensive, and in many cases show poor detection and classification performance,...
In this paper, a frequency domain feature extraction algorithm for face recognition is proposed, which efficiently exploits the local spatial variations in a face image. For the purpose of feature extraction, instead of considering the entire face image, an entropy-based local band selection criterion is developed, which selects high-informative horizontal segments from the face image. In order to...
Information of the urban road areas for resource management, security monitoring, urban development and Geographic Information System (GIS) is changing with the growing world. Satellite image provides useful data that is extracted from satellite image of the urban area. Automatic extraction of the road intersections from the urban areas has been a challenging topic because the high resolution satellite...
A new integrated feature distributions based color textured image segmentation algorithm has been proposed. The proposed scheme uses histogram based new color texture extraction method which inherently combines color texture features rather then explicitly extracting it. Use of non parametric Bayesean clustering makes the segmentation framework fully unsupervised where no a priori knowledge about...
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