Face Detection Based on Graph Structure and Neural Networks

Bashier, Housam Khalifa; Abusham, Eimad Abdu; Khalid, Fatimah

doi:10.3923/tasr.2012.683.691

Cited by 13 publications

(3 citation statements)

References 20 publications

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“…The LGS [26] algorithm is dominated by the dominating set in graph structure. Given an undirected graph G = <V, E>, where V is the point set whose size is n and E is the set of edges, then S, a subset of V, can be called a dominating set if and only if for any point v in V-S, there is a point u of S and (u, v) ∈ E. That is, for any vertex v in G, if v either belongs to D or is adjacent to a vertex in D, then D is called a dominating set of G.…”

Section: Related Theory 21 Lgsmentioning

confidence: 99%

Finger Vein Recognition Based on Multi-Orientation Weighted Symmetric Local Graph Structure

Song¹,

Yang²,

Chen³

et al. 2015

KSII TIIS

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Finger vein recognition is a biometric technology using finger veins to authenticate a person, and due to its high degree of uniqueness, liveness, and safety, it is widely used. The traditional Symmetric Local Graph Structure (SLGS) method only considers the relationship between the image pixels as a dominating set, and uses the relevant theories to tap image features. In order to better extract finger vein features, taking into account location information and direction information between the pixels of the image, this paper presents a novel finger vein feature extraction method, Multi-Orientation Weighted Symmetric Local Graph Structure (MOW-SLGS), which assigns weight to each edge according to the positional relationship between the edge and the target pixel. In addition, we use the Extreme Learning Machine (ELM) classifier to train and classify the vein feature extracted by the MOW-SLGS method. Experiments show that the proposed method has better performance than traditional methods.

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Section: Related Theory 21 Lgsmentioning

confidence: 99%

Finger Vein Recognition Based on Multi-Orientation Weighted Symmetric Local Graph Structure

Song¹,

Yang²,

Chen³

et al. 2015

KSII TIIS

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show abstract

“…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

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-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.

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“…The SLGS [12] takes balanced advantage of the pixels in the right side and left side of target pixel as shown in Fig. 3.…”

Section: Slgsmentioning

confidence: 99%

A New Finger Vein Recognition Method Based on the Difference Symmetric Local Graph Structure (DSLGS)

Song¹,

Yang²,

Wang³

et al. 2015

IJSIP

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Face Detection Based on Graph Structure and Neural Networks

Cited by 13 publications

References 20 publications

Finger Vein Recognition Based on Multi-Orientation Weighted Symmetric Local Graph Structure

Finger Vein Recognition Based on Multi-Orientation Weighted Symmetric Local Graph Structure

Face Spoofing Detection Using Local Graph Structure

A New Finger Vein Recognition Method Based on the Difference Symmetric Local Graph Structure (DSLGS)

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