recognition and enhancement of traffic sign for computer generated images
DESCRIPTION
seminar on Recognition and enhancement of traffic sign for computer generated imagesTRANSCRIPT
SEMINAR ON
RECOGNITION AND ENHANCEMENT OF TRAFFIC SIGN FOR COMPUTER-
GENERATED IMAGES
PRESENTED BY :Shailesh kumar
CONTENT
INTRODUCTION
TECHNOLOGY
WORKING
APPLICATION
FUTURE ASPECT
CONCLUSION
INTRODUCTION
As technology advanced day by day image processing gains huge
development in recent year.
Image enhancement technology is often used to improve image
quality.
Compared with the natural image, significant characteristics for
computer-generated image is simple in overall.
The difficulty is how to accurately recognition and enhance specific
target and maintaining other information of object do not been
changed.
INTRODUCTION(CONTINUED)
Here we consider 256-color indexed image that is generated based o
rendering 3D model.
Combined with the characteristics of the computer-generated image ,
the recognition and enhancement takes series of steps
A. Image preprocessing.
B. Image recognition.
C. Image enhancement.
TECHNOLOGY
Red light camera technology
WORKING
Recognition and Enhancement take series of steps.
A. Image preprocessing
B. Image recognition
C. Image enhancement
A. Image Pre-processing
What is an image?
Image is an array or a matrix, of a square pixels arranged in
columns
And rows.
What it includes(Image preprocessing)?
Smoothing and enhancing the image.
WORKING(CONTINUED)
Recognition of Traffic SignTraffic sign include mark line and dark road. Recognition of Mark Line. Recognition of Dark Road.
Fig 3.1 It shows the mark line and the dark road.
Mark line.
Dark road.
Slope part.
Fig 4.1 Image corrupted with noise.
Fig 4.2 Result smoothed by smoothing
Recognition of mark line
There are two methods first is scan line algorithm and
another is
a series of filtering operation.
Scan line algorithm is used because of its simpleness and
high efficiency.
The 1st binary image is form by performing the algorithm in
horizontal direction and 2nd in vertical direction.
STEPS
1.
2. There are still some mistakes object.
Figure 4.4 The left image is the
result of the step 1, the Right image is result of the step 3, and the contrastive Effect shows in the red circle.
3.
4.The most likely object of the dark road are recognized.
Figure 4.5. The left image is result of the step 1, the right
Image is result of the step
4. The red part within theGreen circle is missing mark line in the step 15. The object of the road surface.
6. The object of non road surface recognized.
7. Figure 4.6.The left
image is the integrated
result in the step 5.The right image is the precise result
8.The object of typical dark road.9. The object of the mark line.
C. Enhancement of traffic sign
B. The recognition of dark road
It having two parts i.e. recognition of flat part and recognition of slope
part
ADVANTAGES AND ITS APPLICATION
Effectively stored and efficiently transmitted.
Digital image processing is easy to implement.
We can remove unwanted objects, adjust exposure,
saturation, hue, levels, sharpness and more.
APPLICATIONS:
Image processing is use in generating images and
for removing noise for the corrupted image.
It is used in detection and enhancement of traffic
sign.
For controlling the traffic light.
Used in various forensic cases Eg. fingerprint
detection
Fig.6.1.Unenhanced image of Fig.6.2.The result of one
enhancement Latent print. Technique use on image
to increase the contrast.
FUTURE ASPECT
Social x-ray
CONCLUSION
In order to enhance the specific target in the computer-generated image
for the actual production requirement.
Experiment and practice demonstrate this project and algorithm are
very effective.
However, in the complex situation, there are some errors. The follow
work is to improve and research enhancement for specific target in
complex situation.
It seems that image recognition and image enhancement is still not
simple process. Therefore, we imagine that image recognition for
complex real scene image also is not simple process. But the idea of
stepwise refinement which is proposed here provides a methodological
reference for complex Image recognition.
REFERENCES
[1]Li Yaping , Zhang Jinfang, Xu Fanjiang“The recognition and
enhancement of traffic sign for the computer-generated image” IEEE
paper, 2012 Fourth International Conference on Digital Home.
[2] “Introduction to computer vision and image processing”, Pdf from
the link www.uotechnology.edu.iq.
[3] Online information provider www.google.com and
www.wikipedia.com.
[4] “Digital Image Processing for Image Enhancement and
Information Extraction” an IEEE international general.
THANK YOU