Research Article | OPEN ACCESS
An In-depth Analysis of Applications of Object Recognition
Abijith Sankar, Akash Suresh, P. Varun Babu, A. Baskar and Shriram K. Vasudevan
Department of Computer Science and Engineering, Amrita School of Engineering,
Amrita University, India
Research Journal of Applied Sciences, Engineering and Technolog 2015 1:1-14
Received: November 7, 2014 | Accepted: February 5, 2015 | Published: May 10, 2015
Abstract
Image processing has become one of the most unavoidable fields of engineering. The way the applications are designed based on Image processing is simply superb. This study is drafted as a study paper aimed at reviewing the object recognition techniques supported in Image Processing Sector. Analyzing object recognition through the applications is a new approach and that is what we have tried through our paper. We have taken effort to check the utilization of Object Recognition techniques in the fields of Industrial applications which includes a. automobiles b. food and beverage sector and c. fabric sector. Then attention is paid towards robotic applications. Remote sensing is also observed to be one of the hottest sectors which deploys objects recognition techniques to a better extent. Finally it is ended up with medicinal applications.
Keywords:
AdaBoost, appearance-based method , feature-based method, filters , fuzzy clustering, gaze determination , genetic algorithm, haar-like structure , head pose, histogram , hyperspectral, image stabilization, machine vision, model-based method , motion compensation, motion estimation,segmentation, SIFT (Scale-Invariant Feature Transform), spectral, spectroscopy, statistical, texture, thresholding,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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The authors have no competing interests.
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