Lab 7

Information

Olivier Rogers: A16069362
Moises Lopez: A14156109

Introduction

In this lab we learned how tho hook up a camera to the pi and we learned methods for detecting text from images by doing some image transfromations and using Tesseract for optical character recognition.

Challenge: Number Plate Detector

Video Demonstration

Approach to finding the area of interest

1. Blur the image to remove high frequencies
2. Pass the image though a canny edge detector
3. Find the contour and sort them by contour area
4. Do polygon approximation for each contour
5. Ignored approximated polygons that are not 4 sided.
6. Pick the first 4 sided poligon, since that is the biggest rectangle in the image.
7. If no rectangle found, send original image to OCR

Tutorial 1: Say Cheese!

In this tutorial we learned to install opencv2 onto the raspberry pi. And learned how to capture a image from a webcam in python.

Tutorial 2: Sudoku Extractor

Tesseract and PyTesseract were installed for OCR. PyTesseract was used with OpenCV to extract a sudoku puzzle from an image.
The default settings did not result in any extracted values. Some things learned:

• Tesseract does not work very well with single characters. Strings are better.
• Changing the psm parameter to 10 instead of 11 improved the single character recognition.
• The current version prefers black text on white backgrounds.
• The best results for this example were obtained on an image with minimal blurring, with threshold applied, and with a little bit of padding on each cropped segment.
• We tried removing the borders (from the Sudoku grid), but that resulted in worse number detection.