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Author

Richa Singh

Bio: Richa Singh is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topic(s): Facial recognition system & Deep learning. The author has an hindex of 53, co-authored 422 publication(s) receiving 9145 citation(s). Previous affiliations of Richa Singh include Indian Institutes of Technology & University of Virginia.
Papers
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DOI
01 Dec 2003
TL;DR: Experimental results show that the proposed algorithm is good enough to localize a human face in an image with an accuracy of 95.18%.
Abstract: In this paper, a detailed experimental study of face detection algorithms based on ”Skin Color” has been made. Three color spaces, RGB, YCbCr and HSI are of main concern. We have compared the algorithms based on these color spaces and have combined them to get a new skin color based face detection algorithm which gives higher accuracy. Experimental results show that the proposed algorithm is good enough to localize a human face in an image with an accuracy of 95.18%.

332 citations


Journal ArticleDOI
Mayank Vatsa1, Richa Singh1, Afzel Noore1Institutions (1)
01 Aug 2008
TL;DR: This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition.
Abstract: This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition. A curve evolution approach is proposed to effectively segment a nonideal iris image using the modified Mumford-Shah functional. Different enhancement algorithms are concurrently applied on the segmented iris image to produce multiple enhanced versions of the iris image. A support-vector-machine-based learning algorithm selects locally enhanced regions from each globally enhanced image and combines these good-quality regions to create a single high-quality iris image. Two distinct features are extracted from the high-quality iris image. The global textural feature is extracted using the 1-D log polar Gabor transform, and the local topological feature is extracted using Euler numbers. An intelligent fusion algorithm combines the textural and topological matching scores to further improve the iris recognition performance and reduce the false rejection rate, whereas an indexing algorithm enables fast and accurate iris identification. The verification and identification performance of the proposed algorithms is validated and compared with other algorithms using the CASIA Version 3, ICE 2005, and UBIRIS iris databases.

272 citations


Proceedings ArticleDOI
23 Jun 2013
TL;DR: A new approach for spoofing detection in face videos using motion magnification using Eulerian motion magnification approach, which improves the state-of-art performance, especially HOOF descriptor yielding a near perfect half total error rate.
Abstract: For a robust face biometric system, a reliable anti-spoofing approach must be deployed to circumvent the print and replay attacks. Several techniques have been proposed to counter face spoofing, however a robust solution that is computationally efficient is still unavailable. This paper presents a new approach for spoofing detection in face videos using motion magnification. Eulerian motion magnification approach is used to enhance the facial expressions commonly exhibited by subjects in a captured video. Next, two types of feature extraction algorithms are proposed: (i) a configuration of LBP that provides improved performance compared to other computationally expensive texture based approaches and (ii) motion estimation approach using HOOF descriptor. On the Print Attack and Replay Attack spoofing datasets, the proposed framework improves the state-of-art performance, especially HOOF descriptor yielding a near perfect half total error rate of 0%and 1.25% respectively.

213 citations


Journal ArticleDOI
Richa Singh1, Mayank Vatsa1, Himanshu Bhatt1, Samarth Bharadwaj1  +2 moreInstitutions (2)
TL;DR: The results on the plastic surgery database suggest that it is an arduous research challenge and the current state-of-art face recognition algorithms are unable to provide acceptable levels of identification performance, so that future face recognition systems will be able to address this important problem.
Abstract: Advancement and affordability is leading to the popularity of plastic surgery procedures. Facial plastic surgery can be reconstructive to correct facial feature anomalies or cosmetic to improve the appearance. Both corrective as well as cosmetic surgeries alter the original facial information to a large extent thereby posing a great challenge for face recognition algorithms. The contribution of this research is 1) preparing a face database of 900 individuals for plastic surgery, and 2) providing an analytical and experimental underpinning of the effect of plastic surgery on face recognition algorithms. The results on the plastic surgery database suggest that it is an arduous research challenge and the current state-of-art face recognition algorithms are unable to provide acceptable levels of identification performance. Therefore, it is imperative to initiate a research effort so that future face recognition systems will be able to address this important problem.

165 citations


Proceedings ArticleDOI
11 Nov 2010
TL;DR: A novel algorithm to recognize periocular images in visible spectrum is proposed and the results show promise towards using peroocular region for recognition when the information is not sufficient for iris recognition.
Abstract: The performance of iris recognition is affected if iris is captured at a distance. Further, images captured in visible spectrum are more susceptible to noise than if captured in near infrared spectrum. This research proposes periocular biometrics as an alternative to iris recognition if the iris images are captured at a distance. We propose a novel algorithm to recognize periocular images in visible spectrum and study the effect of capture distance on the performance of periocular biometrics. The performance of the algorithm is evaluated on more than 11,000 images of the UBIRIS v2 database. The results show promise towards using periocular region for recognition when the information is not sufficient for iris recognition.

158 citations


Cited by
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Journal ArticleDOI

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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

30,199 citations





01 Jun 2005

3,153 citations


Network Information
Related Authors (5)
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Mayank Vatsa

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Afzel Noore

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Arun Ross

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Rama Chellappa

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Performance
Metrics

Author's H-index: 53

No. of papers from the Author in previous years
YearPapers
20222
202136
202036
201946
201851
201740