NDLI: Unrestricted LR detection for biomedical applications using coarse-to-fine hierarchical approach

Content Provider	IET Digital Library
Author	Qasmieh, Isam Abu quran, Hiam Al
Abstract	In this study, the authors present a simple, reliable, fast, unrestricted-shape geometry, and accurate algorithm which runs in O(log2 n) time to find the axis-parallel largest rectangle (LR) inside a given region of interest (ROI), where n is the image size in one dimension, which means that the proposed model can work in real time. The proposed approach is successful in detecting the LR of arbitrary orientation that is fully contained in the ROI as well. Also, the present algorithm can find the largest empty rectangle in a space containing a set of zero points, whether the axis-parallel rectangle or the oriented one. The strategy followed here is to accelerate LR detection process by searching the rectangle with the largest area inscribed in the ROI, by starting first with the lowest-resolution version of the original image for determining the LR four corners’ coordinates, then next searching the new LR corners’ scaled coordinates in the higher power resolutions in a multiple resolutions hierarchical model and therefore, a corresponding coarse-to-fine inference procedure recursively eliminates the search space of the LR four corners coordinates. For finding the largest oriented rectangle, the same hierarchical procedures are followed, but combined with rotation-angle resolution.
Starting Page	1639
Ending Page	1645
Page Count	7
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 9, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0509
Journal	IET Image Processing
Publisher Date	2018-04-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biomedical Application Coarse-to-fine Hierarchical Approach Combinatorial Mathematics Computer Vision And Image Processing Technique Convex-hull Polygon Image Pixel Image Resolution Multiple Resolutions Hierarchical Model Optical, Image And Video Signal Processing Optimisation Technique Search Problem Unrestricted LR Detection
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition 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

Automatic detection of individual and touching moths from trap images by combining contour-based and region-based segmentation

Pedestrian re-identification via coarse-to-fine ranking

Target tracking approach via quantum genetic algorithm

Enhanced mutual information-based medical image registration using a hybrid optimisation technique

Adaptive convolutional neural network for large change in video object segmentation

Coarse-to-fine search technique to detect circles in images (1999).

Fractal triangular search: a metaheuristic for image content search

Vanishing point detection using the teaching learning-based optimisation algorithm

Region-based saliency detection

Unrestricted LR detection for biomedical applications using coarse-to-fine hierarchical approach

Similar Documents

Automatic detection of individual and touching moths from trap images by combining contour-based and region-based segmentation

Pedestrian re-identification via coarse-to-fine ranking

Target tracking approach via quantum genetic algorithm

Enhanced mutual information-based medical image registration using a hybrid optimisation technique

Adaptive convolutional neural network for large change in video object segmentation

Coarse-to-fine search technique to detect circles in images (1999).

Fractal triangular search: a metaheuristic for image content search

Vanishing point detection using the teaching learning-based optimisation algorithm

Region-based saliency detection

Unrestricted LR detection for biomedical applications using coarse-to-fine hierarchical approach