sign language recognition system for deaf and dumb people

1. SIGN RECOGNITION System FOR DEAF AND
DUMB PEOPLE
GUIDED BY PRESENTED BY
Ms.I.KANAGA SANGEETHA M.E
ASSISTANT PROFESSOR M.RINCY JULIET
DEPARTMENT OF ECE (98010106052)
A.SUBACHITHIRAI MEENAL
(98010106068)
M.SURIYA
(98010106072)
Department of ECE

2. OBJECTIVE
To develop a system for automatic translation
of static gestures used by dumb and deaf persons
into audible speech understandable by a common
person.

3. INTRODUCTION
• Sign recognition system act as a interpreter
between common people and socially aided
people.
• It captures the gesture shown by the deaf and
dumb people and convert immediately into
known language.

4. LITERATURE SURVEY 1
Title Sign language recognition system
Author Er.Aditi Kalsh, Dr.N.S.Garewal
Years June 2013
Journal
International Journal of Engineering
Research
Explanation
Canny edge and peak detection is used for feature
extraction.

5. LITERATURE SURVEY 2
Title Real Time Indian Sign Language Recognition System to
aid Deaf and Dumb people
Author Rajam, P. Subha and Dr G Bala krishnan
Years June 2011
Journal 13th International Journal Communication
Technology(ICCT)
Explanation Cam shift and HSV approach for recognizing gesture

6. LITERATURE SURVEY 3
Title SignPro-An Application Suite for Deaf and Dumb
Author Ashish Sethi, Hemanth, Kuldeep kumar
Years
May 2012
Journal
International Journal of Computer Science Engineering
Technology
Explanation
Skin segmentation and region growth approach is used
for image recognition

7. Tools Required
SOFTWARE
MATLAB
HARDWARE
Laptop with external web camera
serial board communication kit

8. BLOCK DIAGRAM
Image
acquisition
Harris corner
detection
Histogram
SIFT
K-NN
Algorithm
Text to speech

9. Harris Corner Detection
• In the harries corner detection we
calculate the cim , r, c.
• Cim - binary image marking corners.
• r - Row coordinates of corner points.
• c - Column coordinates of corner points

10. Histogram
• Histograms can be used to provide
useful image statistics Information
• It plots the number of pixels for each
value
• Histogram we are using the num-bins
function

11. SIFT
Orientation assignment
Key point localization
Scale space Extrema detection

12. K-NN Algorithm
• This approach is used to match the key points
calculated from the capture image using the
harries and sift.
• Now the key points matched with the database
image.
• IDX = knn search searches the reference data
set to find the k-nearest neighbours of each
query point represented by each row.

13. Text to Speech
• Serial board communication kit is used to
convert Text to Speech.
• This Kit contains PIC Microcontroller,
Selector, Voice recorder, Amplifier, Speaker,
Step down transformer.

14. Captured image of sign ‘A’

15. Captured image of sign ‘B’

16. Captured image of sign ‘C’

17. Database images in the folder A ,D
LETTER A
LETTER D

18. database images in the folder B,C
• LETTER B

19. Text Result

20. THANK YOU