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Abstract
Gesture recognition has revolutionized the way of doing things at homes and workplaces by bridging the gap between humans and machine. Gesture recognition technology is getting pace day by day as it has the potential to make human-machine interaction more natural and simpler, and has immense applications like virtual reality, photo browsing, car and home automation . It has the the capability to make human body language understandable to computer[3].This paper primarily focuses on hand gesture recognition .This paper proposes hand gesture recognition of Hindi vowels symbols captured through webcam, which acts as a sign language for conveying information, by using opencv image processing software. There are three steps in this proposed approach: Image capturing, hand tracking and segmentation, and gesture recognition. Hand tracking is accomplished through opencv.
Keywords: Gesture Recognition, Hindi Vowels, hand gesture recognition, opencv, hand tracking.
1.
Introduction
Gesture recognition is a term used for interpreting various human gestures and motions through computing device and algorithms. Gesture is a combination of hand position, orientation and observation at some instance [2].Gesture can originate from movement of body parts like hand, arms, face, lips and even the facial expressions [Wikipedia].Gesture can be static or dynamic. Gesture has its big hand in virtual reality system where traditional way of inputting(keyboard ,mouse) is not used, that is human gesture is used as an input to machine for navigating and controlling environment[3].From various gestures hand gesture is the most intuitive and natural way of communication and we also used various hand gestures in our daily routine unknowingly ,naturally[1].Hand gesture recognition is of utmost importance due to its capability to make human-machine interaction more natural without using any mechanical device, for instance television channels can be changed just by waving hand(hand gesture) without using a remote. Hand gesture recognition is communication through hand that does not require any equipments like data glove. Hand gesture recognition technology makes the computer accessible to speech impaired people in an easy and efficient manner but this is not only for speed impaired people for conveying their information. This is just one scenario as there are lots of other applications of hand gesture recognition like interactive games, virtual reality, etc. Sign language recognition for Hindi vowels is one of the forms of hand gesture recognition where hand gesture is used for making Hindi vowels. Sign language is used by a person for communicating and expressing feelings through gestures. Thus the objective of this paper is recognition of hand gestures of Hindi vowels without using any hardware device like data glove .Aim of the paper is to implement hand gesture recognition of Hindi vowel by using opencv tool of image processing and computer vision technique. Opencv tool implements hand gesture recognition technology by identifying position and orientation of hand in captured image [4].
Fig 1
Fig 1: Shows use of hand gesture for controlling television volume without even touching it. This hand gesture is taken as an input to machine.
2.
Literature Survey
Provide an approach for real time gesture recognition using a camera. For this viola Jones detector is used that transform the time series of the trajectories to angular space which results in scale and translation invariance. Then these series are
Hand Gesture Recognition for Hindi Vowels
Using OpenCV
1
Itisha Gupta, 2Vinti Parmar, 3Shubham Tayal 1IGU, Rewari, India
2F.L.T.M.S.B.P Govt. college for women, Rewari, India 3
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used for gesture recognition to a set of templates using dynamic time warping [1].Provide an approach for real time hand tracking and gesture recognition in unconstrained environment. This paper provides a system having three modules: real time hand tracking, training gesture and gesture recognition using pseudo two dimension hidden Markov models (P2-DHMMs). Kalman filter and hand blobs are used for analysis of hand tracking to obtain motion descriptors and hand region[2].Provide an approach for various gesture recognition technology and various applications of gesture recognition technology. Gesture recognition is the process by which gestures formed by a user are made known to the system. Virtual reality is an application of gesture technology where the keyboard is not included but some other means of controlling environment is needed [3].Provide an approach for building a simple recognizer for yes/no gestures for Wintel platform. This paper focuses on robustness of recognizer and also supports on/off feature in recognizer [4].Provide an approach for survey of gesture recognition with main focus on hand gesture and facial expression recognition. Hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are described in detail. Existing challenges and future research possibilities are also presented [5].Provide an approach for hand gesture recognition using kinect. This paper focuses on a robust algorithm, which can recognize various arrangements of fingers of both hands showing digits from 0 to 5 using a Kinect [6].Provide an approach for Hand Gesture Detection and Recognition for Human-Computer Interaction. Nokia N900 is used for capturing images of hand gestures and used distant transform which is an operator applied to binary images that’s result in transformation in a grayscale image that looks similar to the input image[7].3.
Proposed Work
Gesture recognition is an important research field which interprets various human gestures. There are various ways of hand gesture recognition like FSM approach, HMM model [5] but our proposed work is on hand gesture recognition of Hindi vowels only through opencv tool. Only eleven Hindi vowels are considered in this proposed work which is symbolized using hand gesture clearly. To symbolize each Hindi vowel, gesture originates only from the hand which forms static gesture set, like our dummy database. Hand tracking and segmentation is primary step of our proposed work. Only after the hand gesture recognition, querying with database is done.
Fig 2: Shows eleven Hindi vowels
3.1 Static hand gesture set symbolizing Hindi vowels (Database)
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This paper focuses only on Hindi vowel recognition so in our proposed work we have the database of only Hindi vowels that are symbolized through hand gesture. Webcam is used for acquiring the hand gesture of each Hindi vowel and then stored in database for recognition process. This database has eleven hand gestures symbolizing each Hindi vowel as shown in table1. Signer wears a full sleeves shirt so as not to complicate recognition process and no other restriction is forced on signer.3.2 Methodology
Overall workflow of our proposed work is divided into 3 steps. First of all hand gestures symbolizing Hindi vowels are captured using webcam. Proposed system uses desktop or laptop webcam as user interface for capturing hand gesture without use of any data glove. In second step hand tracking and segmentation is performed using opencv software. Hand tracking and segmentation requires a lot of things to be accomplished so step by step process is given below:-
Eliminate the background to make the image more appealing and clear [6] for further recognition process as there is no need of background and other body part. It also eliminates noise.
Dilation and erosion (sister of dilation) of image is done. It results in further clearing of image as these operations remove spot and noise in region.
Next step is detection of edges that is contour extraction for minimizing complexity and calculations. Contour is outline of each edge that is contour represent line or curve in inputted image [7] so opencv functions are used for detecting contours and contour having largest area denotes hand.
Then using opencv functions convex hull and defects points of hand shape are calculated for tracking palm position and no of fingers.
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Output
Fig 4: Overall workflow4.
Conclusion
This paper proposes a novel and easy approach for hand gesture recognition of Hindi vowels and then uses this gesture for sign language recognition. Proposed work focuses only on hand gesture recognition of eleven Hindi vowels .Since hand tracking is the primary step in gesture recognition so using various functions of opencv software hand tracking is accomplished. Various methods like Background elimination, contour extraction, calculation of convex hull and defect points using opencv helps in hand gesture recognition. In future, system will be stretched out for recognition of gesture other than hand and also expanded for Hindi consonant recognition.
References
[1] A system for real time gesture recognition Daniel persson and Bjorn samvik Master’s thesis 2009:E14 Faculty of Engineering Centre for Mathematical Sciences Mathematics
[2] Real-Time Hand Tracking and Gesture Recognition System Nguyen Dang Binh, Enokida Shuichi, Toshiaki Ejima Intelligence Media Laboratory, Kyushu Institute of Technology 680-4, Kawazu, Iizuka, Fukuoka 820, Japan [ndbinh, enokida, toshi]@mickey.ai.kyutech.ac.jp
[3] The Journal of Computer Science and Information Technology ISSN 0973-4872, Vol. 3, No.1 (2006) pp. 86-88 Institute of Technology & Management GESTURE RECOGNITION TECHNOLOGY Anupma Yadav Dept. of CSE & IT Institute of Technology & Management, Gurgaon
[4] Gesture recognition Ondřej Novák, František Ondřej, Jan Ondřej OpenCV
Set up environment for recognition
Capture image through webcam
Background elimination
Dilation and erosion of image
Palm and finger extraction
Querying with database
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[5] Gesture Recognition: A Survey Sushmita Mitra, Senior Member, IEEE, and Tinku Acharya, Senior Member, IEEE [6] hand gesture recognition using kinect Boston University Department of Electrical and Computer Engineering 8 SaintMary’s Street Boston, MA 02215 www.bu.edu/ece December 15, 2011 Technical Report No. ECE-2011-04
