An optimal set of image segmentation rules

Authors:
Martin D Levine;Ahmed M Nazif
Affiliations:
Computer Vision and Robotics Laboratory, Department of Electrical Engineering, McGill University, Montreal, Quebec, Canada H3A 2A7;Department of Electrical Engineering, Cairo University, Cairo, Egypt
Venue:
Pattern Recognition Letters
Year:
1984

Citing 1
Cited 1

Low Level Image Segmentation: An Expert System

IEEE Transactions on Pattern Analysis and Machine Intelligence

Image interpretation with a conceptual graph: Labeling over-segmented images and detection of unexpected objects

Artificial Intelligence

Quantified Score

Hi-index	0.10

Visualization

Abstract

A set of rules for segmenting images was selected based on a quantitative evaluation of performance using a rule-based system. This note presents the rules and summarizes the results of their application.