FACE DETECTION USING GABOR FILTERS AND NEURAL NETWORKS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

MAHLOUJI M.; MOHAMMADIAN R.

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR Year:2015 | Volume:13 | Issue:1 Page(s): 1-13

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,538

Download:

Cites:

Information Journal Paper

Title

FACE DETECTION USING GABOR FILTERS AND NEURAL NETWORKS

Author(s)

MAHLOUJI M. | MOHAMMADIAN R. | Issue Writer Certificate

Keywords

FACE DETECTIONQ2

NEURAL NETWORKQ2

GABOR FILTERQ2

GABOR FEATURESQ2

Abstract

In this paper, a robust method for FACE DETECTION from different views using a combination of GABOR FILTERs and NEURAL NETWORKs is presented. First, a mathematical equation of GABOR FILTER is expressed. Then, by examining 75 different filter banks, range of effective parameters values in GABOR FILTER generation is determined, and finally, the best value for them is specified. The NEURAL NETWORK used in this paper is a feed-forward back-propagation multilayer perceptron network. The input vector of the NEURAL NETWORK is obtained from the convolution the input image and a GABOR FILTER with angles p / 2 and the frequency p / 2 in the frequency domain. The proposed method has been tested on 550 image samples from Feret database with simple background and Markus Weber database with complex background, and detection accuracy of them is 98.4% and 95%, respectively. Also, the face area has been detected using Viola-Jones algorithm, and then comparison between the results obtained from Viola-Jones algorithm and the proposed method is described.

Cites

MULTI-HUMAN FACE DETECTION USING GABOR FILTERS AND NEURAL NETWORKS IN INTERNET IMAGES

References

No record.

Cite

APA: Copy

MAHLOUJI, M., & MOHAMMADIAN, R.. (2015). FACE DETECTION USING GABOR FILTERS AND NEURAL NETWORKS. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, 13(1), 1-13. SID. https://sid.ir/paper/228433/en

Vancouver: Copy

MAHLOUJI M., MOHAMMADIAN R.. FACE DETECTION USING GABOR FILTERS AND NEURAL NETWORKS. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR[Internet]. 2015;13(1):1-13. Available from: https://sid.ir/paper/228433/en

IEEE: Copy

M. MAHLOUJI, and R. MOHAMMADIAN, “FACE DETECTION USING GABOR FILTERS AND NEURAL NETWORKS,” NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, vol. 13, no. 1, pp. 1–13, 2015, [Online]. Available: https://sid.ir/paper/228433/en

Related Journal Papers