NDLI: Extremal Regions Detection Guided by Maxima of Gradient Magnitude

Content Provider	IEEE Xplore Digital Library
Author	Faraji, M. Shanbehzadeh, J. Nasrollahi, K. Moeslund, T.B.
Copyright Year	1992
Abstract	A problem of computer vision applications is to detect regions of interest under different imaging conditions. The state-of-the-art maximally stable extremal regions (MSERs) detects affine covariant regions by applying all possible thresholds on the input image, and through three main steps including: (1) making a component tree of extremal regions' evolution; (2) obtaining region stability criterion; and (3) cleaning up. The MSER performs very well, but, it does not consider any information about the boundaries of the regions, which are important for detecting repeatable extremal regions. We have shown in this paper that employing prior information about boundaries of regions results in a novel region detector algorithm that not only outperforms MSER, but avoids the MSER's rather complicated steps of enumeration and the cleaning up. To employ the information about the region boundaries, we introduce maxima of gradient magnitudes (MGMs) which are shown to be points that are mostly around the boundaries of the regions. Having found the MGMs, the method obtains a global criterion for each level of the input image which is used to find extremum levels (ELs). The found ELs are then used to detect extremal regions. The proposed algorithm which is called extremal regions of extremum levels (EREL) has been tested on the public benchmark data set of Mikolajczyk. The obtained experimental results show that the inclusion of region boundaries through MGMs, results in a detector that detects regions with high repeatability scores and is more robust against noise compared with MSER.
Sponsorship	IEEE Signal Processing Society
Starting Page	5401
Ending Page	5415
Page Count	15
File Size	13220826
File Format	PDF
ISSN	10577149
Volume Number	24
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stability criteria Detectors Histograms Image edge detection Computer vision Cleaning Feature Detection Maxima of Gradient Magnitude (MGM) Maximally Stable Extremal Region (MSER) Extremal Regions of Extremum Levels (EREL) feature detection Maxima of gradient magnitude (MGM) maximally stable extremal region (MSER) extremal regions of extremum levels (EREL)
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

EREL: Extremal regions of extremum levels

Shape Guided Maximally Stable Extremal Region (MSER) Tracking

Shape Guided Maximally Stable Extremal Region (MSER) Tracking

CGSR features: Toward RGB-D image matching using color gradient description of geometrically stable regions

Multi-sensor image registration using edge-enhanced maximally stable extremal region

Efficient Maximally Stable Extremal Region (MSER) Tracking

Efficient maximally stable extremal region (mser) tracking

Shape Descriptors for Maximally Stable Extremal Regions

Robust text detection in natural images with edge-enhanced Maximally Stable Extremal Regions

Extremal Regions Detection Guided by Maxima of Gradient Magnitude

Similar Documents

EREL: Extremal regions of extremum levels

Shape Guided Maximally Stable Extremal Region (MSER) Tracking

Shape Guided Maximally Stable Extremal Region (MSER) Tracking

CGSR features: Toward RGB-D image matching using color gradient description of geometrically stable regions

Multi-sensor image registration using edge-enhanced maximally stable extremal region

Efficient Maximally Stable Extremal Region (MSER) Tracking

Efficient maximally stable extremal region (mser) tracking

Shape Descriptors for Maximally Stable Extremal Regions

Robust text detection in natural images with edge-enhanced Maximally Stable Extremal Regions

Extremal Regions Detection Guided by Maxima of Gradient Magnitude