A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Scale and the differential structure of images
Image and Vision Computing - Special issue: information processing in medical imaging 1991
Topographic distance and watershed lines
Signal Processing - Special issue on mathematical morphology and its applications to signal processing
Global Minimum for Active Contour Models: A Minimal Path Approach
International Journal of Computer Vision
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Minimal path algorithms for the robust detection of linear features in gray images
ISMM '98 Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
A Benchmark: Performance Evaluation of Dashed-Line Detection Algorithms
Selected Papers from the First International Workshop on Graphics Recognition, Methods and Applications
Dynamic Programming
IEEE Transactions on Parallel and Distributed Systems
A software architecture for user transparent parallel image processing
Parallel Computing - Parallel computing in image and video processing
Fast Anisotropic Gauss Filtering
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Efficient Applications in User Transparent Parallel Image Processing
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Incorporating memory layout in the modeling of message passing programs
Journal of Systems Architecture: the EUROMICRO Journal - Special issue: Parallel, distributed and network-based processing
IEEE Transactions on Parallel and Distributed Systems
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Detection of individual specimens in populations using contour energies
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Performing real-time image processing on distributed computer systems
MUSP'10 Proceedings of the 10th WSEAS international conference on Multimedia systems & signal processing
Parallel image and video processing on distributed computer systems
WSEAS Transactions on Signal Processing
User transparent task parallel multimedia content analysis
Euro-Par'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part II
Towards user transparent parallel multimedia computing on GPU-Clusters
ISCA'10 Proceedings of the 2010 international conference on Computer Architecture
User Transparent Data and Task Parallel Multimedia Computing with Pyxis-DT
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Contour energy features for recognition of biological specimens in population images
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
User transparent data and task parallel multimedia computing with Pyxis-DT
Future Generation Computer Systems
Hi-index | 0.00 |
The extraction and interpretation of networks of lines from images yields important organizational information of the network under consideration. In this paper, a one-parameter algorithm for the extraction of line networks from images is presented. The parameter indicates the extracted saliency level from a hierarchical graph. Input for the algorithm is the domain specific knowledge of interconnection points. Graph morphological tools are used to extract the minimum cost graph which best segments the network.We give an extensive error analysis for the general case of line extraction. Our method is shown to be robust against gaps in lines, and against spurious vertices at lines, which we consider as the most prominent source of error in line detection. The method indicates detection confidence, thereby supporting error proof interpretation of the network functionality. The method is demonstrated to be applicable on a broad variety of line networks, including dashed lines. Hence, the proposed method yields a major step towards general line tracking algorithms.