Fast hand detection and gesture recognition

Wang, Yuh-Rau; Syu, Jia-Liang; Li, Hsin-Ting; Yang, Ling

doi:10.1109/icmlc.2015.7340956

Cited by 5 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wang, Syu, Li and Yang [5] employed symmetric mask based discrete wavelength transform to reduce the computational time by 66%. Ankita Saxena, Deepak Jain and Ananya Singhal developed [6] hand gesture recognition system for an android device using sobel algorithm and back propagation neural network. Rahat Yasir and Riasat Azim Khan [7] proposed a twohanded hand gesture recognition system for Bangla sign language using linear discriminant analysis (LDA) and artificial neural network.…”

Section: Introductionmentioning

confidence: 99%

Sign Language Gesture Recognition System for Hearing Impaired People

Prabhu¹,

Dessai²

2018

IJCA

View full text Add to dashboard Cite

The hand gesture is one of a powerful means of communication among human. Sign language is an essential and natural expressive mean of communication for the deaf people. American sign language helps the hearing-impaired people to communicate with the world as well as the computer. This paper proposes a technique for the recognition of American alphabet sign language. The technique of image processing, that is singular value decomposition (SVD), is applied in order to extract characteristics of the hand images performing individual alphabet of American sign language. The decomposed singular values extracted from the image are used to classify the image into one of the ASL alphabets. These SV features are then applied to SVM classifier for gesture recognition. The totals of 26 American sign language gestures are used in the experiments. This procedure is executed on a database with a total of 899 images of static American sign language gestures taken under different background and lighting conditions. The recognition rate of the proposed technique at about 74 % is achieved.

show abstract

Section: Introductionmentioning

confidence: 99%

Sign Language Gesture Recognition System for Hearing Impaired People

Prabhu¹,

Dessai²

2018

IJCA

View full text Add to dashboard Cite

show abstract

“…Among major colour spaces such as RGB [34], HSV [35], or YIQ [36], our system uses YCbCr colour space for thresholding to distinguish between skin and non-skin colours. Indeed, the YCbCr colour space is the most popular choice in skin-colour detection methods, because its luminance component Y as well as chrominance components Cb and Cr are separated and could be easily computed from RGB values [37].…”

Section: A Skin-colour Detectionmentioning

confidence: 99%

HD: Efficient Hand Detection and Tracking

Rouge

Shaikh

Olszewska

2016

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

Abstract-Automated hand detection is useful for applications requiring reliable hand posture and hand gesture processing. Such applications include human-computer/human-robot interfaces for rehabilitation, serious games, or non-invasive medical diagnosis. Hence, in this paper, we focus on the design and development of a robust and fast hand detection and tracking (HD) system. The design of our HD system involved the study of the human skin colour and people's foreground properties, in order to merge these information for an efficient hand detection and tracking. Experiments have been carried out in real-world environment and have demonstrated the excellent performance of our HD system.

show abstract

Comprehensive Review of various Hand Detection Approaches

Gulati

Bhogal

2018

2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)

View full text Add to dashboard Cite

Fast hand detection and gesture recognition

Cited by 5 publications

References 8 publications

Sign Language Gesture Recognition System for Hearing Impaired People

Sign Language Gesture Recognition System for Hearing Impaired People

HD: Efficient Hand Detection and Tracking

Comprehensive Review of various Hand Detection Approaches

Contact Info

Product

Resources

About