Robust Line Hausdorff Distance for Face Recognition

Dang-Nguyen, Chau; Do-Hong, Tuan

doi:10.1109/isee2.2019.8921218

Cited by 5 publications

(6 citation statements)

References 10 publications

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“…In our previous work [1], a new data structure of LEM was proposed. Due to the angle between line segments and the horizontal axis, the line segments in LEM are grouped into N groups and 180/N degrees for each group.…”

Section: Lts-lhd For Face Recognitionmentioning

confidence: 99%

“…In the rest of this section, the recognition rate of the proposed method is compared with the LHD method in [27] and the RLHD method in [1], using average HD for measuring the dissimilarity between LEMs.…”

Section: Influence Of Parameter K On the Performancementioning

confidence: 99%

“…The advantage of HD is that there is no requirement of point-to-point correspondence. In many science and engineering fields, HD has particular attention of researcher, such as face recognition [1][2][3][4][5], image matching [6][7][8], image segmentation for medical image [9][10][11], image retrieval [12,13], shape matching [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…Based on LHD, the extension of LHD, called spatial weighted line segment Hausdorff distance (SWLHD), was presented for face recognition [28] . In our previous work [1], we proposed a modification of LHD for face recognition, called Robust Line Hausdorff distance RLHD.…”

Section: Introductionmentioning

confidence: 99%

“…Here we propose an extension of the method in [1], called Least trimmed square Line Hausdorff distance (LTS-LHD) for face recognition. The LTS-LHD, an extension of weighted average HD, is used for measuring the dissimilarity between two line edge maps (LEMs).…”

Section: Introductionmentioning

confidence: 99%

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Application of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition

Dang-Nguyen¹

2020

Adv. sci. technol. eng. syst. j.

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The Hausdorff distance (HD) is defined as MAX-MIN distance between two geometric objects for measuring the dissimilarity between two objects. Because MAX-MIN distance is sensitive with the outliers, in face recognition field, average Hausdorff distance is used for measuring the dissimilarity between two sets of features. The computational complexity of HD, and also average HD, is high. Various methods have been proposed in recent decades for reducing the computational complexity of HD computing. However, these methods could not be used for reducing the computational complexity of average HD. Line Hausdorff distance (LHD) is a face recognition method, which uses weighted average HD for measuring the distance between two line edge maps of face images. In this paper, the Least Trimmed Square Line Hausdorff Distance method, LTS-LHD, is proposed for face recognition. The LTS-LHD, which is a modification of the weighted average HD, is used for measuring the distance between two line edge maps. The state-of-art algorithm, the EARLYBREAK method, is used for reducing the computational complexity of the LTS-LHD. The experimental results show that the accuracy of proposed method and LHD method are equivalent while the runtime of proposed method is 68% lower than LHD method.

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Section: Lts-lhd For Face Recognitionmentioning

confidence: 99%

Section: Influence Of Parameter K On the Performancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Application of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition

Dang-Nguyen¹

2020

Adv. sci. technol. eng. syst. j.

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A Faulty Feeder Selection Method based on Improved Hausdorff Distance Algorithm for Neutral Non-effectively Grounded System

Zhang

Qiao

et al. 2022

Electric Power Systems Research

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An improved Hausdorff distance method for locating single phase to ground fault in neutral non‐effectively grounded system

Zhang

et al. 2021

IET Generation Trans & Dist

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Neutral non-effectively grounded mode is widely used in medium-voltage distribution networks in China. When a single-phase grounding fault occurs in distribution networks, abundant transient signals will be generated. Here, a fault location method based on improved Hausdorff distance is proposed with transient zero-sequence current and transient zero-sequence voltage of bus. First, according to the impedance characteristic analysis of the zero-sequence network, the selected frequency band (SFB) is determined, and the transient signals in the SFB are extracted by the digital filter. Second, the projection components of transient zero-sequence currents at each monitoring point of faulty feeder are obtained by the principle of orthogonalization. Finally, the projection component values of each section are calculated by the improved Hausdorff distance, and the maximum value is selected. If the maximum value is much larger than the sum of the values of other sections excluding the maximum value, the section where the maximum value is located is judged as a faulty section, otherwise, the downstream section of the last monitoring point is determined as the faulty section. Matlab/Simulink simulation shows that the proposed method can locate accurately under different fault conditions.

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Robust Line Hausdorff Distance for Face Recognition

Cited by 5 publications

References 10 publications

Application of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition

Application of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition

A Faulty Feeder Selection Method based on Improved Hausdorff Distance Algorithm for Neutral Non-effectively Grounded System

An improved Hausdorff distance method for locating single phase to ground fault in neutral non‐effectively grounded system

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