Extracting straight lines by sequential fuzzy clustering

Authors:
Koji Tsuda;Michihiko Minoh;Katsuo Ikeda
Affiliations:
-;-;-
Venue:
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Year:
1996

Citing 3
Cited 4

Extracting straight lines

IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual Organization for Scene Segmentation and Description

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Metric for Line Segments

IEEE Transactions on Pattern Analysis and Machine Intelligence

Fuzzy PCA-guided robust k-means clustering

IEEE Transactions on Fuzzy Systems
Collaborative filtering by sequential user-item co-cluster extraction from rectangular relational data

International Journal of Knowledge Engineering and Soft Data Paradigms
Browsing and similarity search of videos based on cluster extraction from graphs

PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Carried object detection and tracking using geometric shape models and spatio-temporal consistency

ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In clustering line segments into a straight line, threshold-based methods such as hierarchical clustering are often used. The line segments comprising a straight line often get misaligned due to noise. Threshold-based methods have difficulty clustering such line segments. A new cluster extraction method is proposed to cope with this problem. This method extracts fuzzy clusters one by one using matrix computation. We evaluated our clustering method using hand-written drawings and obtained promising results.