Recognition and enhancement of traffic sign for computer generated images
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This document discusses recognition and enhancement of traffic signs in computer-generated images. It presents a multi-step process including image preprocessing, recognition, and enhancement. Image preprocessing involves smoothing and enhancing. Recognition identifies traffic signs like road markings and dark roads using techniques like scan line algorithms and filtering. Enhancement improves identified signs by increasing contrast. The process is effective but further improvement is needed to handle complex situations. Applications include traffic control and forensic analysis.
![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.](https://image.slidesharecdn.com/recognitionandenhancementoftrafficsignforcomputer-generatedimages-140331054102-phpapp01/85/Recognition-and-enhancement-of-traffic-sign-for-computer-generated-images-16-320.jpg)
Recognition and enhancement of traffic sign for computer generated images
- 1. RECOGNITION AND ENHANCEMENT OF TRAFFIC SIGN FOR COMPUTER- GENERATED IMAGES PRESENTED BY : Shailesh kumar
- 2. CONTENT INTRODUCTION TECHNOLOGY WORKING APPLICATION FUTURE ASPECT CONCLUSION
- 3. 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.
- 4. 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.
- 5. TECHNOLOGY Red light camera technology
- 6. 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.
- 7. WORKING(CONTINUED) Recognition of Traffic Sign Traffic 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.
- 8. 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.
- 9. 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.
- 10. 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 the Green circle is missing mark line in the step 1 5. 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
- 11. 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
- 12. 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
- 13. Fig.6.1.Unenhanced image of Fig.6.2.The result of one enhancement Latent print. Technique use on image to increase the contrast.
- 15. 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.
- 16. 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.