Detection of ridges and ravines using fuzzy logic operations
Pattern Recognition Letters
Estimation of Average Cell Shape from Digital Images of Cellular Surfaces
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
An architectural level design methodology for embedded face detection
CODES+ISSS '05 Proceedings of the 3rd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
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Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
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ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
WSEAS Transactions on Computers
WSEAS Transactions on Computers
View reconstruction from images by removing vehicles
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics
Adaptive 3D texture streaming in M3G-based mobile games
Proceedings of the 3rd Multimedia Systems Conference
Detecting humans under partial occlusion using Markov logic networks
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
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ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Vehicle re-identification collaborating visual and temporal-spatial network
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Hierarchical fuzzy logic based approach for object tracking
Knowledge-Based Systems
Two-dimensional multi-pixel anisotropic Gaussian filter for edge-line segment (ELS) detection
Image and Vision Computing
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We propose an approach to accurately detecting two-dimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-dimensional (1-D) optimal step edge operator, which minimizes both the noise power and the mean squared error between the input and the filter output. This operator is found to be the derivative of the double exponential (DODE) function, originally derived by Ben-Arie and Rao (1994). We define an operator for shape detection by extending the DODE filter along the shape's boundary contour. The responses are accumulated at the centroid of the operator to estimate the likelihood of the presence of the given shape. This method of detecting a shape is in fact a natural extension of the task of edge detection at the pixel level to the problem of global contour detection. This simple filtering scheme also provides a tool for a systematic analysis of edge-based shape detection. We investigate how the error is propagated by the shape geometry. We have found that, under general assumptions, the operator is locally linear at the peak of the response. We compute the expected shape of the response and derive some of its statistical properties. This enables us to predict both its localization and detection performance and adjust its parameters according to imaging conditions and given performance specifications. Applications to the problem of vehicle detection in aerial images, human facial feature detection, and contour tracking in video are presented.