NDLI: Latent Semantic Analysis (LSA) based object recognition and clustering

Content Provider	IEEE Xplore Digital Library
Author	Hebballi, V. Rojit, V.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., PES Inst. of Technol., Bangalore, India (Hebballi, V.; Rojit, V.)
Abstract	Object Recognition and clustering are major techniques in Pattern Recognition, Computer Vision, Artificial Intelligence and Robotics. Conventionally these techniques are implemented in Visual-Feature based methods and Cosine Similarity method or Vector Space method which uses semantic similarity among the objects to solve these kinds of problem, but this method has two problems synonymy and polysemy. In synonymy many ways to refer to the same objects for e.g. car and automobile, which leads to poor recall. Similarly, in polysemy most words have more than one meaning, e.g. model, python and chip, which leads to poor precision. In this paper, we propose a method which will overcome the problems like synonymy and polysemy. If the text printed on the object the semantic feature of that object is extracted and clustered according to Latent Semantic Analysis (LSA). The Proposed method is based on semantic information so an experiment is conducted with the dataset of images which contains the packing cases of commercial products (e.g. Mobile, Laptop etc). Semantic information in the dataset is retrieved using text extraction modules and then the results of text extraction are passed through an Internet search module. Finally, objects are recognized and clustered using the LSA module. The clustering results are more accurate than cosine similarity or vector space method.
Starting Page	416
Ending Page	421
File Size	621603
Page Count	6
File Format	PDF
e-ISBN	9781467379106
DOI	10.1109/ICGCIoT.2015.7380499
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-08
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Symmetric matrices Object Recognition Semantics Clustering algorithms Image Processing Feature extraction Internet Object Clustering Text Mining Object recognition Optical character recognition software
Content Type	Text
Resource Type	Article

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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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