Real-time hand-tracking on video image based on palm geometry

Wirayuda, Tjokorda Agung Budi; Adhi, Habbi Ananto; Kuswanto, Didik Hari; Dayawati, Retno Novi

doi:10.1109/icoict.2013.6574580

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…Competitive hand valley detection (CHVD): This method performs four conditions on all pixels in the hand image. Only the pixels satisfying four conditions at the same time are determined to be candidate KPs [39].…”

Section: Non-contact Palmprint Segmentation and Localizationmentioning

confidence: 99%

Key Point Localization Based on Intersecting Circle for Palmprint Preprocessing in Public Security

Zhou¹,

Chen²,

Leng³

2019

J. Def. Acquis. Technol.

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Secure identity authentication is important in defense technology fields and public security. Palmprint is a good biometric modality used for authentication on mobile devices. Unfortunately, the background of palmprint image collected with mobile devices is random and changeable. Usually, the region of interest is localized based on the key points of the inter-finger-valley. In order to resist the random and variable background interference and effectively remove the false inter-finger-valley contours, this paper develops a key point localization method based on intersecting circle for palmprint preprocessing. Since the contour curvature of inter-finger-valley is greater than that of the rest of the hand, each contour point is taken as the center of an intersecting circle, and the radius of the intersecting circle is set according to the finger width. The developed method can determine the set of candidate contour points at the inter-finger-valley. The remained false inter-finger-valley contour points are further removed according to the direction of the central angle. The bottom point of the contour at the inter-finger-valley is used as the key point. The sufficient experiments show that the method in this paper is less dependent on the segmentation effect, and it is robust to false contour and background interference, so the localization and recognition accuracies are high.

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Section: Non-contact Palmprint Segmentation and Localizationmentioning

confidence: 99%

Key Point Localization Based on Intersecting Circle for Palmprint Preprocessing in Public Security

Zhou¹,

Chen²,

Leng³

2019

J. Def. Acquis. Technol.

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show abstract

“…Median filtering is conducted to reduce noise effect especially in boundary area. In algorithm CHVD there are four conditions which have to be fulfilled to get wanted valley pixel [4,5]:…”

Section: A First-stage Preprocessingmentioning

confidence: 99%

Palm print recognition using competitive hand valley detection, local binary pattern and probabilistic neural network

Wibawa

Agung

Sthevanie

2014

2014 International Conference on Information Technology Systems and Innovation (ICITSI)

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Biometric is a method to iden the specific feature based on part Nowadays, biometric is widely used performance to identify human. The pa used in this research were manually coll of 110 people with 10 images for each p recognition system consist of : region extraction using Competitive Hand (CHVD) method, feature extraction pro Binary Pattern (LBP) method and clas using Probabilistic Neural Network research we proposed area segmentati LBP that consist of overlap and non-ove using segmentation the feature will beca and distinctive. In 60 people (50 known the best system accuracy achieve was 9 110 people (100 known and 10 unknown) achieve was 91.91%. The best performan with four overlap segment schemas, 8 che smoothing parameter set at 0.03.

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Palmprint Identification and Verification System Based on Euclidean Distance and 2D Locality Preserving Projection Method

Ali

Gaikwad

Yannawar

2018

Advances in Intelligent Systems and Computing

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Real-time hand-tracking on video image based on palm geometry

Cited by 4 publications

References 6 publications

Key Point Localization Based on Intersecting Circle for Palmprint Preprocessing in Public Security

Key Point Localization Based on Intersecting Circle for Palmprint Preprocessing in Public Security

Palm print recognition using competitive hand valley detection, local binary pattern and probabilistic neural network

Palmprint Identification and Verification System Based on Euclidean Distance and 2D Locality Preserving Projection Method

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