Computer don't have the ability to process the videos and images on their own like humans. We can interpret any kind of images to a large extent but the machines lack this ability.
Computer Vision gives them this ability to interpret digital images and videos. Computer Vision is about teaching the computer to see and interpret and process these images for better understanding. Computer Vision is about how computer can gain high level of understanding from digital images.
Field of Use:
- Self Driving Cars
- Facial Recognition
- Malicious object detection for security purpose
OpenCV is an open source computer vision library for image processing, Machine Learning. It is a cross platform library.Some of its use cases are:
- It includes interfaces for C, C++, Java, and Python
- It is used to process static images
- It is also used to process offline videos and/or streaming videos
Tesseract OCR is an optical character recognition engine, which has the ability to recognize words and text files.
In this project I have used OpenCV
and Tesseract OCR
to process a text image to detect the words in the image.
The project work includes
urllib.request
moduleWhen the image is loaded it is read using imread()
function from the cv2
module.
The image read by the imread function is by default in BGR
format and needs to be converted to Gray
scale image before processing for better text recognition.
After the image is converted into the desired scale of colors it is resized and then using the Gaussian Blur
technique it is formatted.
After formatting of the image, the image is then passed through the Tesseract OCR
to return a string which is then processed to return the final text contained in the image.
I NEVER DREAMED ABOUT SUCCESS. I WORKED FOR IT
My love said she would marry only me
And Jove himself could not make her care.
For what women say to lovers, you'll agree
lone writes on running water or on air.
Sin of self-love possesseth all mine eye
And all my soul and all my every part;
land for this sin there is no remedy,
It is so grounded inward in my heart.