NDLI: A Run-Based Two-Scan Labeling Algorithm

Please wait, while we are loading the content...

Unified Anomaly Suppression and Boundary Extraction in Laser Radar Range Imagery based on a Joint Curve-Evolution and Expectation-Maximization Algorithm

Self-Repelling Snakes for Topology-Preserving Segmentation Models

Segmentation by Fusion of Histogram-Based $K$-Means Clusters in Different Color Spaces

Using Spanning Graphs for Efficient Image Registration

Block-Coordinate Gauss–Newton Optimization and Constrained Monotone Regression for Image Registration in the Presence of Outlier Objects

Infinite Hidden Markov Models for Unusual-Event Detection in Video

Continuous Sampling in Mutual-Information Registration

IEEE Transactions on Image Processing EDICS

IEEE Transactions on Image Processing Information for authors

Have you visited lately? www.ieee.org [advertisement]

IEEE copyright form

IEEE Signal Processing Society Information

Year : 2007 Volume : 16

Year : 2006 Volume : 15

Year : 2005 Volume : 14

Year : 2004 Volume : 13

Year : 2003 Volume : 12

Year : 2002 Volume : 11

Year : 2001 Volume : 10

Year : 2000 Volume : 9

Year : 1999 Volume : 8

Year : 1998 Volume : 7

Year : 1997 Volume : 6

Year : 1996 Volume : 5

Year : 1995 Volume : 4

Year : 1994 Volume : 3

Year : 1993 Volume : 2

Year : 1992 Volume : 1

A Run-Based Two-Scan Labeling Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Lifeng He Yuyan Chao Suzuki, K.
Copyright Year	1992
Abstract	We present an efficient run-based two-scan algorithm for labeling connected components in a binary image. Unlike conventional label-equivalence-based algorithms, which resolve label equivalences between provisional labels, our algorithm resolves label equivalences between provisional label sets. At any time, all provisional labels that are assigned to a connected component are combined in a set, and the smallest label is used as the representative label. The corresponding relation of a provisional label and its representative label is recorded in a table. Whenever different connected components are found to be connected, all provisional label sets concerned with these connected components are merged together, and the smallest provisional label is taken as the representative label. When the first scan is finished, all provisional labels that were assigned to each connected component in the given image will have a unique representative label. During the second scan, we need only to replace each provisional label by its representative label. Experimental results on various types of images demonstrate that our algorithm outperforms all conventional labeling algorithms.
Sponsorship	IEEE Signal Processing Society
Page Count	8
File Size	645114
Starting Page	749
Ending Page	756
File Format	PDF
ISSN	10577149
Volume Number	17
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Labeling Pixel Chaos Pattern recognition Image edge detection Encoding Pattern analysis Image recognition Computer vision run-length encoding Connected components labeling algorithm linear-time algorithm pattern recognition
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Two Efficient Label-Equivalence-Based Connected-Component Labeling Algorithms for 3-D Binary Images

Efficient scan mask techniques for connected components labeling algorithm

A Very Fast Algorithm for Simultaneously Performing Connected-Component Labeling and Euler Number Computing

Fast and Memory Efficient 2-D Connected Components Using Linked Lists of Line Segments

A fast connected components labeling algorithm and its application to real-time pupil detection

Optimized Block-Based Connected Components Labeling With Decision Trees

Configuration-Transition-Based Connected-Component Labeling

Light speed labeling: efficient connected component labeling on RISC architectures

Comparative evaluation of linear edge detection methods

A Run-Based Two-Scan Labeling Algorithm

Similar Documents

Two Efficient Label-Equivalence-Based Connected-Component Labeling Algorithms for 3-D Binary Images

Efficient scan mask techniques for connected components labeling algorithm

A Very Fast Algorithm for Simultaneously Performing Connected-Component Labeling and Euler Number Computing

Fast and Memory Efficient 2-D Connected Components Using Linked Lists of Line Segments

A fast connected components labeling algorithm and its application to real-time pupil detection

Optimized Block-Based Connected Components Labeling With Decision Trees

Configuration-Transition-Based Connected-Component Labeling

Light speed labeling: efficient connected component labeling on RISC architectures

Comparative evaluation of linear edge detection methods

A Run-Based Two-Scan Labeling Algorithm