1. 研究專題研究專題 老師：賴薇如教授學生：吳家豪 學號： 907133

2. Outline Background of Image Processing Explain to The Algorithm of Image Processing Experiments Conclusion References

3. Background of Image Processing Image processing, analysis and machine vision represent an exciting and dynamic part of cognitive and computer science. Following an explosion of interest during the 1970s to 2000s were characterized by the maturing of field and the significant growth of active application.

4. Background of Image Processing General image processing usually use at machine vision, medical imaging, vehicle guidance … etc. It has been done by: Color or grey weight Edge information Shape form

5. Explain to The Algorithm of Image Processing Edge detection An edge is the boundary between two regions with relatively distinct gray-level properties. Most edge detection techniques is the computation of a local derivative operator. Edge detection provides post processing with meaningful information.

6. Explain to The Algorithm of Image Processing Most edge detection use filter convolution operator result image R: i*j pixels original image z: i*j pixels operation mask w: (2*n+1)*(2*n+1) pixels

7. First Derivative 1.Get first derivative 2.Set threshold and get edge problem: –How to set threshold? –Maybe have non-maximum value. –Pool edge of detection.

8. Second Derivative 1.Get first derivative 2.Get edge problem: –It have some problem with noise

9. Experiments First Derivative x _weight y _weight

10. Experiments Second Derivative

11. Experiments Canny edge

12. Conclusion In image processing field, analysis and pattern recognition … etc are extreme difficult as well as human vision because of digital image and computer algorithm which different from human.

13. References Image processing, Analysis, and Machine Vision Milan Sonkka, Vaclav Hlavac, Roger Boyle Digital Image Processing Rafael C. Gonzalez, Richard E. Woods