Results 251 to 260 of about 5,151,122 (293)

Hardware-determined feature edges

Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering, 2004
Algorithms that detect silhouettes, creases, and other edge based features often perform per-edge and per-face mesh computations using global adjacency information. These are unsuitable for hardware-pipeline implementation, where programmability is at the vertex and pixel level and only local information is available.
Morgan McGuire, John F. Hughes
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Fuzzy classification of generic edge features

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002
This paper presents a fuzzy logic approach for classifying generic edge segments (GES). A set of GES is modeled in descriptive geometry based on perceptual organization principles. Each GES represents a class of edge segments which belong to a same perceptual group and measured according to the generic criteria of perceptual organization laws.
QiGang Gao, Dan Qing, Siwei Lu
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Noise, edge extraction, and visibility of features

SPIE Proceedings, 2005
Noise, whether due to the image-gathering device or some other reason, reduces the visibility of fine features in an image. Several techniques attempt to mitigate the impact of noise by performing a low-pass filtering operation on the acquired data. This is based on the assumption that the uncorrelated noise has high-frequency content and thus will be ...
Zia-ur Rahman 0001, Daniel J. Jobson
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Band-edge features in disordered systems

Physical Review B, 1985
Despite the complexity of real disordered materials, the electronic properties often have similar features in dissimilar materials, suggesting the presence of universal features, particularly near band edges. In the present paper, we demonstrate that under certain conditions, including weak disorder, band-edge features are universal for fewer than two ...
, Cohen, , Economou, , Soukoulis
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Improving edge-based feature extraction using feature fusion

2008 IEEE International Conference on Systems, Man and Cybernetics, 2008
Feature extraction is arguably the most important stage of an automatic object detection system. It is in this stage where the results of previous processing steps are interpreted to somehow characterize an object. Developing methods for feature extraction and feature vector generation using information from edge maps is a natural progression, as edge ...
Shahan C. Nercessian, Karen A. Panetta, Sos S. Agaian   +2 more
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Perceptual tracking of edge features

Proceedings of 1st International Conference on Image Processing, 2002
Presents an approach for extracting edge features directly from grey-level images. The approach is based on the principle of perceptual organization, which simulates to human visual process on edge perception in certain aspects. >
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A review of edge computing: Features and resource virtualization

Journal of Parallel and Distributed Computing, 2021
Abstract With the advent of Internet of Things (IoT) connecting billions of mobile and stationary devices to serve real-time applications, cloud computing paradigms face some significant challenges such as high latency and jitter, non-supportive location-awareness and mobility, and non-adaptive communication types.
Yaser Mansouri, Muhammad Ali Babar 0001
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Classification of Depth and Surface Edges with Deep Features

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Edges in 2D images fall into two categories: depth edges and surface edges, depending on if the edge corresponds to an abrupt change in depth (the distance from the camera). This edge type is an efficient, robust, and effective information in many applications. In this paper we study the problem of automatic classification of the two types of edges. We
Zhenhao Li 0001, Xiaolin Wu 0001
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Feature Edge Extraction Via Angle-Based Edge Collapsing and Recovery

Journal of Computing and Information Science in Engineering, 2018
This paper presents a new method for extracting feature edges from computer-aided design (CAD)-generated triangulations. The major advantage of this method is that it tends to extract feature edges along the centroids of the fillets rather than along the edges where fillets are connected to nonfillet surfaces.
Soji Yamakawa, Kenji Shimada
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Multi-feature edge extraction with local fractal features

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region, 2004
The local fractal dimension (LFD) is proposed to extract local fractal features of gray-scale images. The definition of LFD is an extension of the pixel-covering method, based on the wavelet-based fractal dimension. Multi-feature edge extraction is implemented with the local fractal features and the image intensity discontinuities.
null Xiaodong Zhuang, null Qingchun Meng
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