1. Shri Ramdeobaba College of Engineering
and Management Nagpur
DEPARTMENT OF ELECTRONICS ENGINEERING
GESTURE RECOGNITION SYSTEM USING
LABVIEW

2. GUIDANCE BY:
PROF. (MRS) M.HASAMNIS
PRESENTED BY:
Roll No Section Candidate Name
46 C GIRISH MORANKAR
61 C PRANOV MUNDHADA
65 C RAHUL VAIDYA
69 C SARANG TAMHANEY

3. AIM
To design a system which will recognize
the hand gestures of deaf-dumb people
and display them into text form using
Labview.

4. OBJECTIVE
To design an efficient and reliable system
which will help deaf and dumb people to
reduce their dependence on human
translators.

5. Block diagram

6. Image
Acquisition
Acquiring an image: in the first step we are
acquiring an image from an controlled
environment. For this a 5 mega pixel camera
(always focused) in 1280 x 576 mjpg 30.0 fps video
mode is used.
We can configure the various attributes of camera
such as contrast ,sharpness ,gain, smoothening
,exposure, white balance etc.

7. Pre-
processing
Template Matching: Template is region of
interest(ROI) in an image which can be processed
irrespective of it's position, orientation and size in the
image. Matching is then performed by finding the
best similarity between the feature vector extracted
from the image to the feature vectors in the template
set.
Color plane extraction: Color plane extraction is
done to remove the redundant information from
the acquired image. Here in this step ,green
plane is extracted from the image.
Set Coordinates: Once the template matching
step is complete we can set the co-ordinate
system by setting the origin at the center of the
template. This origin is used as a reference for all
other parameters of the image. We have used
Cartesian co-ordinate system.

8. Green plane
extraction
Template used
Setting coordinates

9. Feature
vector
extraction
Contour Detection: Contour is the outline
of figure or body or edge that bounds or
defines a shape or object. in this step five
contour detectors are assigned to positions
of fingers with reference to the template.

10. Feature extraction from
database
 Now the challenge before us is
to map the alphabets from the
database. For this, we are using
weighted position system.
 We have assigned weights to
each of the five contour
positions. since the output of
contour will be a analog value.
2^4=16
2^3 =8
2^2 =4
2^1 =2
2^0=1

11.  Now well be converting those output of contours into
binary logic(1 or 0)and concatenate them in an array.
 Then we’ll covert this binary no into its equivalent
decimal number.
Binary no Decimal equivalent Mapped digit
00001 8 1
11000 24 2
11100 28 3
01111 15 4
11111 31 5
00111 7 6

12. Flowchart
Image
acquisition
Colour plane
extraction
Template
matching
Set co-
ordinates
Contour
detection
Comparison of
feature vector
to database
Mapping
alphabets

13. Tools Used:
1. LabVIEW
 It is a professional development system.
 It is a graphical programming environment used
to develop sophisticated measurement, test, and
control systems.

14. 2. Vision Assistant
 Vision Assistant is a tool for processing acquired image.
 To prototype an image processing application, we
have build customized algorithms with the Vision
Assistant scripting feature. The scripting feature records
every step of the processing algorithm. After
completing the algorithm, you can test it on other
images to make sure it works.
 Using the LabVIEW VI Creation Wizard, you can create
a LabVIEW VI program that performs the prototype that
you created in Vision Assistant.

15. 3.Vision Builder
 It is used for automated inspection.
 It gives you an easy way to deploy a system that
addresses vision applications from pattern matching to
code reading and presence detection to precision
alignment and classification.
 It is interactive development environment that replaces
the complexities of programming, making the
development and maintenance process simple with
range of functionality.

16. THANK YOU