A Novel Approach for Saliency Detection by using Stationary Wavelet Transform Low Level Features

Mulagundla Mahalaxmi; Dr. M.N. Giri prasad; Dr. K. Manjunathachari

A Novel Approach for Saliency Detection by using Stationary Wavelet Transform Low Level Features

Mulagundla Mahalaxmi * §

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Dr. M.N. Giri prasad

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Dr. K. Manjunathachari

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§ Vardhaman College of Engineering

A Novel Approach for Saliency Detection by using Stationary Wavelet Transform Low Level Features

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Abstract

The ability of the Human Visual System (HVS) to detect an object in an image is extremely fast and reliable but how can a machine vision system detects the salient regions? many algorithms have been proposed to solve this problem by extracting features in either spatial or spectral domain, in this paper, A novel saliency detection model is introduced by utilizing low level features obtained from Stationary Wavelet Transform domain. Here Stationary Wavelet Transform (SWT) is preferred as the wavelet transform than Discrete Wavelet Transform (DWT), Since DWT is not a time-invariant transform. So to make it translation invariant SWT is introduced. And also unlike the other wavelet transforms SWT does not require down sampling, So image size is same as original even after decomposition, thus there is no information loss in respective sub bands. Experimental results demonstrate that proposed model produces better performance by using SWT than by using DWT with the overall F-Measure value being high.

References

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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

Mulagundla Mahalaxmi, Dr. prasad, Dr. Manjunathachari. 2015. "A Novel Approach for Saliency Detection by using Stationary Wavelet Transform Low Level Features". Global Journal of Research in Engineering, Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 14 (GJRE Volume 14 Issue J6).

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GJRE Volume 14 Issue J6

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

feature map human visual system (HVS)saliency detection saliency map stationary wavelet transform

Classification

GJRE-J Classification FOR Code: 091599

Submission ReceivedDecember 13, 2013
Peer Review Double Blind
Handling Editor
Accepted January 3, 2014
Published January 15, 2014

Version of record

v1.2

Issue date

January 6, 2015

Language

English

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Article Matrices

Total Score: 114

Country: India

Subject: Global Journal of Research in Engineering

Authors: Mulagundla Mahalaxmi, Mr K. Durga prasad, Dr. K. Manjunathachari, Dr. M.N. Giri prasad (PhD/Dr. count: 2)

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