Contactless Palm Vein ROI Extraction using Convex Hull Algorithm

Jhinn, Wee Lorn; Goh, Michael Kah Ong; Lau, Siong Hoe; Connie, Tee

doi:10.1007/978-981-13-2622-6_3

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…We used the entire palm as the ROI. The convex-hull method described in [21] was used to identify the thumb and finger tips of a palm image, while image contours and thresholding were used to extract a binary matte of the palm and used with an erosion filter to use as a mask to filter out the feature points reside closer to the edges. This method produces variable sized ROI images.…”

Section: Experiments and Resultsmentioning

confidence: 99%

A Novel Image Enhancement Method for Palm Vein Images

Perera

Khelifi

Belatreche

2022

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)

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Palm vein images usually suffer from low contrast due to skin surface scattering the radiance of NIR light and image sensor limitations, hence require employing various techniques to enhance the contrast of the image prior to feature extraction. This paper presents a novel image enhancement method referred to as Multiple Overlapping Tiles (MOT) which adaptively stretches the local contrast of palm vein images using multiple layers of overlapping image tiles. The experiments conducted on the CASIA palm vein image dataset demonstrate that the MOT method retains the finer subspace details of vein images which allows excellent feature detection and matching with SIFT and RootSIFT features. Results on existing palm vein recognition systems demonstrate that the proposed MOT method delivers lower EER values outperforming other existing palm vein image enhancement methods.

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Section: Experiments and Resultsmentioning

confidence: 99%

A Novel Image Enhancement Method for Palm Vein Images

Perera

Khelifi

Belatreche

2022

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)

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show abstract

“…For the experiments, all the images were first downsampled by 60%, and the entire palm was used for the region of interest (ROI), which produced variable sized ROIs. Thumbs and fingertips were identified using the convex-hullbased approach presented by [22]. A binary image was extracted by thresholding and using image contours, which were then applied with an erosion filter to produce a mask.…”

Section: Experiments and Resultsmentioning

confidence: 99%

A Keypoint Filtering Method for SIFT-based Palm-Vein Recognition

Perera

Khelifi

Belatreche

2022

2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA)

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A key issue with palm vein images is that slight movements of fingers and the thumb or changes in the hand pose can stretch the skin in different areas and alter the vein patterns. This can produce palm vein images with an infinite number of variations for a given subject. This paper presents a novel filtering method for SIFT-based feature matching referred to as the Mean and Median Distance (MMD) Filter, which checks the difference of keypoint coordinates and calculates the mean and the median in each direction in order to filter out the incorrect matches. Experiments conducted on the 850nm subset of the CASIA dataset show that the proposed MMD filter can maintain correct points and reduce false positives that were detected by other filtering methods. Comparison against existing SIFT-based palm vein recognition systems demonstrates that the proposed MMD filter produces excellent performance recording lower Equal Error Rate (EER) values.

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Rotation-Invariant Palm ROI Extraction for Contactless Recognition

Nguyen

Horng

2021

Advances in Computer Vision and Computational Biology

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Contactless Palm Vein ROI Extraction using Convex Hull Algorithm

Cited by 3 publications

References 14 publications

A Novel Image Enhancement Method for Palm Vein Images

A Novel Image Enhancement Method for Palm Vein Images

A Keypoint Filtering Method for SIFT-based Palm-Vein Recognition

Rotation-Invariant Palm ROI Extraction for Contactless Recognition

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