A Collaborative approach for segmentation of probe image for efficient texture recognition

Divya Mathur; Sandeep Upadhyay

A Collaborative approach for segmentation of probe image for efficient texture recognition

Divya Mathur * § Masters of Technology

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Sandeep Upadhyay

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§ Techno India NJR Institute of Technology

A Collaborative approach for segmentation of probe image for efficient texture recognition

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CST9232D

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Abstract

Image processing methodologies and domain is quite wide and really efficient now days for real time applications. Our work primarily deals with the domain of image segmentation and using segmentation concept, texture recognition has been performed with comparative results and simulations performed over a particular image dataset. The initial work in our proposed work is to perform segmentation on each part image then performing extraction .We have focused on segmentation followed by extraction so that the classification result may not contain much error. The conventional approach has been implemented in this regard first and then the main problem that has been formulated is patch up data pixels together which provide error in getting right and appropriate texture. In order to deal with the problem formulated in the existing work we have proposed a new commuted method in which the extraction and segmentation of image depends on the dynamic threshold set by user.

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2 Cites in Article

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Arindam Chaudhuri,Krupa Mandaviya,Pratixa Badelia,Soumya Ghosh (2017). Optical Character Recognition Systems.
Debasish Basa,Sukadev Meher Handwritten Odia Character Recognition.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Divya Mathur, Sandeep Upadhyay. 2019. "A Collaborative approach for segmentation of probe image for efficient texture recognition". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 19 (GJCST Volume 19 Issue C1).

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GJCST Volume 19 Issue C1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-C Classification I.7.5

Submission ReceivedDecember 12, 2018
Peer Review Double Blind
Handling Editor
Accepted December 31, 2018
Published January 15, 2019

Version of record

v1.2

Issue date

April 16, 2019

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Divya Mathur, Sandeep Upadhyay (PhD/Dr. count: 0)

View Count (all-time): 361

Total Views (Real + Logic): 1255

Total Downloads (simulated): 83

Publish Date: 2019 01, Tue

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Total Views: 1.3K

Total Downloads: 83

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