Implementation of a labeling algorithm based on contour tracing with feature extraction

Hugo Hedberg, Fredrik Kristensen, Viktor Öwall

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

This paper describes an architecture of a connected-cluster labeling algorithm for binary images based on contour tracing with feature extraction. The implementation is intended as a hardware accelerator in a self contained real-time digital surveillance system. The algorithm has lower memory requirements compared to other labeling techniques and can guarantee labeling of a predefined number of clusters independent of their shape. In addition, features especially important in this particular application are extracted during the contour tracing with little increase in hardware complexity. The implementation is verified on an FPGA in an embedded system environment with an image resolution of 320 × 240 at a frame rate of 25 fps. The implementation supports labeling of 61 independent clusters, extracting their location, size and center of gravity. © 2007 IEEE.
Original languageEnglish
Title of host publication[Host publication title missing]
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages1101-1104
DOIs
Publication statusPublished - 2007
Event2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 - New Orleans, LA, United States
Duration: 2007 May 272007 May 30

Publication series

Name
ISSN (Print)0271-4310
ISSN (Electronic)2158-1525

Conference

Conference2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007
Country/TerritoryUnited States
CityNew Orleans, LA
Period2007/05/272007/05/30

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering

Free keywords

  • Contour tracing
  • Hardware complexity
  • Labeling techniques
  • Labeling algorithms

Fingerprint

Dive into the research topics of 'Implementation of a labeling algorithm based on contour tracing with feature extraction'. Together they form a unique fingerprint.

Cite this