Detecting objects in images in real-time computer vision systems using structured geometric models

Authors:
A. A. Boguslavskii;S. M. Sokolov
Affiliations:
Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia 125047;Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia 125047
Venue:
Programming and Computing Software
Year:
2006

Citing 11
Cited 0

Extracting straight lines

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
On Detecting Edges

IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Detection of Dominant Points on Digital Curves

IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to algorithms

Introduction to algorithms
The Douglas-Peucker algorithm for line simplification: re-evaluation through visualization

Computer Graphics Forum
Digital image processing

Digital image processing
Techniques for Assessing Polygonal Approximations of Curves

IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Processing of Line-Drawing Images

ACM Computing Surveys (CSUR)
Use of the Hough transformation to detect lines and curves in pictures

Communications of the ACM
An Introduction to the Kalman Filter

An Introduction to the Kalman Filter

Quantified Score

Hi-index	0.00

Visualization

Abstract

Methods for designing high-level image processing algorithms for real-time computer vision systems (VS) in which images of objects or their parts can be represented using structured geometric models that have step-like edge features as their primitive elements.