Abstract:
Our revolutionary method extracts characters from number plate images. We utilized various image preparation methods to extract only text from number plate image. Images are prone to noise and other undesirable items.
Effective noise removal removes image noise. Before picture preprocessing, RGB image is transformed to gray scale and scaled to maintain aspect ratio. Morphological processing improves text detection. Images are doubled. Image intensity is boosted using edge detection. Item gaps are filled. Image may have several horizontal and vertical lines after edge detection.
These lines should be deleted from image to extract text alone. These picture preparation steps leave a few minor undesirable artifacts. Unwanted items are deleted. Bounding boxes is applied to text extracted. These texts are images. These visuals become characters. Systems retrieve characters from images using optical character recognition.
Directory contains character and numeric graphics. Bounding boxes separate extracted text images. Each enclosing box contains a character or number. Each character or integer is scaled to directory image. Compare extracted picture to character image characteristic. Characters shown after comparison. Then recognized characters are displayed in text.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
Did you like this final year project?
To download this project Code with thesis report and project training... Click Here
