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Probabilistic Relaxation Labeling: A Short Survey on Object Recognition

by Abbas Zohrevand
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 38
Year of Publication: 2019
Authors: Abbas Zohrevand
10.5120/ijca2019918387

Abbas Zohrevand . Probabilistic Relaxation Labeling: A Short Survey on Object Recognition. International Journal of Computer Applications. 181, 38 ( Jan 2019), 40-44. DOI=10.5120/ijca2019918387

@article{ 10.5120/ijca2019918387,
author = { Abbas Zohrevand },
title = { Probabilistic Relaxation Labeling: A Short Survey on Object Recognition },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2019 },
volume = { 181 },
number = { 38 },
month = { Jan },
year = { 2019 },
issn = { 0975-8887 },
pages = { 40-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number38/30285-2019918387/ },
doi = { 10.5120/ijca2019918387 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:08:32.743308+05:30
%A Abbas Zohrevand
%T Probabilistic Relaxation Labeling: A Short Survey on Object Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 38
%P 40-44
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Object recognition problem can be defined as classifying input object(s) to number of predefined classes. Object recognition is one of the most important sections in computer vision. While this filed has been studied from long time ago, but it still suffers from several challenges such as: occlusion, rotation, distortion illumination, and scaling. The conventional object recognition system has two phases. Firstly: extraction of the most important (informatics or key pints) parts from object image (scene image) and predefined class image (model image), secondly matching between object and model. The Probabilistic Relaxation Labeling (PRL) is one of the popular probabilistic approaches in matching among model and scene. In this paper we review two phase and report the most important works based PRL.

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Index Terms

Computer Science
Information Sciences

Keywords

Object recognition Probabilistic Relaxation Labeling image descriptor model image scene image.

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