4,911 research outputs found

    Fuzzy Clustering for Image Segmentation Using Generic Shape Information

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    The performance of clustering algorithms for image segmentation are highly sensitive to the features used and types of objects in the image, which ultimately limits their generalization capability. This provides strong motivation to investigate integrating shape information into the clustering framework to improve the generality of these algorithms. Existing shape-based clustering techniques mainly focus on circular and elliptical clusters and so are unable to segment arbitrarily-shaped objects. To address this limitation, this paper presents a new shape-based algorithm called fuzzy clustering for image segmentation using generic shape information (FCGS), which exploits the B-spline representation of an object's shape in combination with the Gustafson-Kessel clustering algorithm. Qualitative and quantitative results for FCGS confirm its superior segmentation performance consistently compared to well-established shape-based clustering techniques, for a wide range of test images comprising various regular and arbitrary-shaped objects

    A Modified Distortion Measurement Algorithm for Shape Coding

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    Efficient encoding of object boundaries has become increasingly prominent in areas such as content-based storage and retrieval, studio and television post-production facilities, mobile communications and other real-time multimedia applications. The way distortion between the actual and approximated shapes is measured however, has a major impact upon the quality of the shape coding algorithms. In existing shape coding methods, the distortion measure do not generate an actual distortion value, so this paper proposes a new distortion measure, called a modified distortion measure for shape coding (DMSC) which incorporates an actual perceptual distance. The performance of the Operational Rate Distortion optimal algorithm [1] incorporating DMSC has been empirically evaluated upon a number of different natural and synthetic arbitrary shapes. Both qualitative and quantitative results confirm the superior results in comparison with the ORD lgorithm for all test shapes, without any increase in computational complexity

    Time division access feasibility study modulation and synchronization considerations

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    Time division access system for satellite communications, and figure of merit for effects of bit and frequency synchronizatio

    Executive Function Deficits in Patients with Mild Cognitive Impairment: Exploring the Impact of Substance Use

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    Substance use is pervasive in the United States. With overdose deaths on the rise for the past decade, studies have examined the detrimental effects of a range of substances. Substance use has been shown to affect the domains of executive functioning, while diseases such as Human Immunodeficiency Virus (HIV) and Hepatitis-C (Hep-C) have been shown to increase the severity of these deficits when comorbid with substance use. Alzheimer’s Dementia (AD) also affects many of the same domains of executive functioning as substance use. However, because of the rapid degenerative nature of the disease, individuals clinically determined to have Mild Cognitive Impairment (MCI) with a risk of progression to AD are more uniform in symptom presentation and discerned deficits, and are therefore more feasible to examine. This study examined whether a history of substance abuse impairs executive function in a cumulative manner when comorbid with MCI with a clinically indicated risk of progression to AD. While those subject to both MCI and substance use history did have the lowest scores in all of the assessments and in each of the conditions measured, those differences were insignificant. The hypothesis was not supported, even though the trend in scores was in the predicted trajectory. These results and implications are discussed, while limitations and possible future research directions are outlined
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