recognition and enhancement of traffic sign for computer generated images

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