Texture classification via extended local graph structure

Bashier, Housam Khalifa; Lau, Siong Hoe; Hui, Liew Tze; Azli, Mohd Fikri; Pang, Ying Han; Kwee, Wee Kouk; Sayeed, Shohel

doi:10.1016/j.ijleo.2015.10.096

Cited by 32 publications

(12 citation statements)

References 10 publications

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“…The extension of LBP known as Local Graph Structure (LGS), and its extended version was introduced in face liveness detection by Housam et al [19,20].…”

Section: Related Workmentioning

confidence: 99%

Face Liveness Detection Using Dynamic Local Ternary Pattern (DLTP)

Parveen

Ahmad²,

Abbas

et al. 2016

Computers

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Abstract:Face spoofing is considered to be one of the prominent threats to face recognition systems. However, in order to improve the security measures of such biometric systems against deliberate spoof attacks, liveness detection has received significant recent attention from researchers. For this purpose, analysis of facial skin texture properties becomes more popular because of its limited resource requirement and lower processing cost. The traditional method of skin analysis for liveness detection was to use Local Binary Pattern (LBP) and its variants. LBP descriptors are effective, but they may exhibit certain limitations in near uniform patterns. Thus, in this paper, we demonstrate the effectiveness of Local Ternary Pattern (LTP) as an alternative to LBP. In addition, we adopted Dynamic Local Ternary Pattern (DLTP), which eliminates the manual threshold setting in LTP by using Weber's law. The proposed method was tested rigorously on four facial spoof databases: three are public domain databases and the other is the Universiti Putra Malaysia (UPM) face spoof database, which was compiled through this study. The results obtained from the proposed DLTP texture descriptor attained optimum accuracy and clearly outperformed the reported LBP and LTP texture descriptors.

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“…The extension of LBP known as Local Graph Structure (LGS), and its extended version was introduced in face liveness detection by Housam et al [19,20].…”

Section: Related Workmentioning

confidence: 99%

Face Liveness Detection Using Dynamic Local Ternary Pattern (DLTP)

Parveen

Ahmad²,

Abbas

et al. 2016

Computers

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“…The proposed LBP-based spiral topology descriptors are compared with the other state-of-the-art methods: binarised statistical image features (BSIF) [21], local energy pattern (LEP) [22], noise-resistant LBP (NRLBP riu2 ) [23], multi-scale joint encoding of LBP (MSJLBP) [24], pairwise rotation invariant cooccurrence LBP (PRICoLBP) [25], extended local graph structure (ELGS) [26] and dominant rotated LBP (DRLBP) [27] in Table 3. The number of neighbour samples P is set to 8 for comparisons.…”

Section: Resultsmentioning

confidence: 99%

Some variants of spiral LBP in texture recognition

Kazak

Koç

2018

IET Image Processing

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“…The graph structure of LGS represents more left-handed neighbor pixels than right-handed ones. To overcome this defect, Extended Local Graph Structure (ELGS) operator is proposed [7]. The procedure for ELGS is based on using the LGS texture descriptor to build two descriptions (horizontally and vertically) and then combine them into a global description.…”

Section: Lbp(imentioning

confidence: 99%

Local feature extraction based facial emotion recognition: a survey

Slimani¹,

Kas²,

Merabet³

et al. 2020

IJECE

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Notwithstanding the recent technological advancement, the identification of facial and emotional expressions is still one of the greatest challenges scientists have ever faced. Generally, the human face is identified as a composition made up of textures arranged in micro-patterns. Currently, there has been a tremendous increase in the use of local binary pattern based texture algorithms which have invariably been identified to being essential in the completion of a variety of tasks and in the extraction of essential attributes from an image. Over the years, lots of LBP variants have been literally reviewed. However, what is left is a thorough and comprehensive analysis of their independent performance. This research work aims at filling this gap by performing a large-scale performance evaluation of 46 recent state-of-the-art LBP variants for facial expression recognition. Extensive experimental results on the well-known challenging and benchmark KDEF, JAFFE, CK and MUG databases taken under different facial expression conditions, indicate that a number of evaluated state-of-the-art LBP-like methods achieve promising results, which are better or competitive than several recent state-of-the-art facial recognition systems. Recognition rates of 100%, 98.57%, 95.92% and 100% have been reached for CK, JAFFE, KDEF and MUG databases, respectively.

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Texture classification via extended local graph structure

Cited by 32 publications

References 10 publications

Face Liveness Detection Using Dynamic Local Ternary Pattern (DLTP)

Face Liveness Detection Using Dynamic Local Ternary Pattern (DLTP)

Some variants of spiral LBP in texture recognition

Local feature extraction based facial emotion recognition: a survey

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