1 / 9

License Plate Recognition

License Plate Recognition. By: Tyler Boraski CSCI Major/Math Minor Clark University 12/14/12. Goal. To be able to read characters off a license plate from a webcam feed. This is a difficult problem for computers, because they can’t read words like we do.

ratana
Télécharger la présentation

License Plate Recognition

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. License Plate Recognition By: Tyler Boraski CSCI Major/Math Minor Clark University 12/14/12

  2. Goal • To be able to read characters off a license plate from a webcam feed. • This is a difficult problem for computers, because they can’t read words like we do. • I simply wanted to challenge myself to see if I could actually do it.

  3. Overview • Two step system • License plate locator • Uses color edge detection to find a Massachusetts license plate. • Character reader • License plate is cropped and sent through Tesseract.

  4. Methods • License Plate Locator • Get image from web feed • Image is converted to HSV • Image is then run through a Sobel filter • If there are teal edges in the resulting image, then we have a license plate candidate.

  5. Methods • Character recognizer • Once our license plate candidate is found, we try to crop it out of the image. • This is then sent through Tesseract-OCR • Hopefully, the string of the license plate is then returned.

  6. Experiments • I found two sample license plates online to test my program. • I simply moved them both around my webcam feed to see how well it worked.

  7. Results • It works!!!!.....sorta • Tesseract is VERY sensitive to it’s input image. • It produces incorrect results the majority of the time. • But, it CAN produce correct results, which is a step in the right direction.

  8. Resulting Limitations • Edge detection only works if license plate is still or almost still. • Tesseract only produces the correct output when the license plate is held a certain distance from the webcam.

  9. Conclusion • This is a much more difficult task that I had imagined. • The locator module is what is causing Tesseract to output weird strings. • If rewritten using contours and connected-component analysis, the result can be greatly improved. • Time for a demo!

More Related