Illumination Normalization using Eimad-housam Technique

Abusham, Eimad; Bashier, Housam Khalifa; Khalid, Fatimah; Sayeed, Shohel; Hossen, J.; Kalaiarasi, S.

doi:10.3923/tasr.2012.692.700

Cited by 3 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many applications have been considered in the literature such face tracking, recognition, plant identification and others extensions of LGS [11][12][13][14][15] but none of them have paid attention to use LGS for face anti-spoofing. Hence, our target in the study is to implement LGS for face anti-spoofing.…”

Section: Related Workmentioning

confidence: 99%

Face Spoofing Detection Using Local Graph Structure

Bashier¹,

Lau²,

Pang³

et al. 2014

Proceedings of the 2014 International Conference on Computer, Communications and Information Technology

Self Cite

View full text Add to dashboard Cite

-Face spoofing attack is one of the recent security traits that face recognition systems are proven to be vulnerable to. The spoofing occurs when an attacker bypass the authentication scheme by presenting a copy of the face image for a valid user. Therefore, it's very easy to perform face recognition spoofing attack with compare to other biometrics. This paper, addresses the problem of detecting imposter face image from live image. In practically, we address this problem from texture analysis point of view because the printed face usually has less quality defect that can be observed by extracting texture features. We adopt Local graph structure LGS to extract the features. Moreover, LGS is based on applying a dominant graph into the input image and it's proved to be a powerful texture operator. Finally, extensive experimental analysis on NUAA showed an encouraging performance.

show abstract

Section: Related Workmentioning

confidence: 99%

Face Spoofing Detection Using Local Graph Structure

Bashier¹,

Lau²,

Pang³

et al. 2014

Proceedings of the 2014 International Conference on Computer, Communications and Information Technology

Self Cite

View full text Add to dashboard Cite

show abstract

Face Spoofing Detection Based on Improved Local Graph Structure

Housam

Lau²,

Pang³

et al. 2014

2014 International Conference on Information Science &Amp; Applications (ICISA)

View full text Add to dashboard Cite

Image Processing Technique for the Detection of Alberseem Leaves Diseases Based on Soft Computing

Abusham

2021

airdj

View full text Add to dashboard Cite

Detecting plant diseases using the traditional method such as the naked eye can sometimes lead to incorrect identification and classification of the diseases. Consequently, this traditional method can strongly contribute to the losses of the crop. Image processing techniques have been used as an approach to detect and classify plant diseases. This study aims to focus on the diseases affecting the leaves of al-berseem and how to use image processing techniques to detect al-berseem diseases. Early detection of diseases important for finding appropriate treatment quickly and avoid economic losses. Detect the plant disease is based on the symptoms and signs that appear on the leaves. The detection steps include image preprocessing, segmentation, and identification. The image noise is removed in the preprocessing stage by using the MATLAB features energy, mean, homogeneity, and others. The k-mean-clustering is used to detect the affected area in leaves. Finally, KNN will be used to recognize unhealthy leaves and determines disease types (fungal diseases, pest diseases (shall), leaf minor (red spider), and deficiency of nutrient (yellow leaf)); these four types of diseases will detect in this thesis. Identification is the last step in which the disease will identify and classified.

show abstract

Illumination Normalization using Eimad-housam Technique

Cited by 3 publications

References 14 publications

Face Spoofing Detection Using Local Graph Structure

Face Spoofing Detection Using Local Graph Structure

Face Spoofing Detection Based on Improved Local Graph Structure

Image Processing Technique for the Detection of Alberseem Leaves Diseases Based on Soft Computing

Contact Info

Product

Resources

About