Download Project Document/Synopsis
Image can be captured in different illumination condition. So if text images are captured in different illumination effect. It is not possible to read the text in image format. Here we proposed a system where text image captured in any illumination condition can be extracted in MATLAB using optical character extraction. Here we use image processing tools to extract text from image. The main aim is to extract the characters in various illumination conditions. Text will be in printed paper. We will capture the image of printed paper. We use effective algorithm to extract characters from printed paper. This system scans the text by evaluating each and every line. Here we will implement this system using MATLAB computation software with image processing toolbox. System will extract word from image using image processing toolbox. As image is captured by webcam or camera. So image is more prone to noise and other environmental interference. In order to extract text from image we will be using thresholding method. Image pre-processing steps are applied on images. Unwanted objects are removed. Bounding boxes is applied to text extracted. These text are in image format. These images are converted to characters. System uses optical character recognition to extract characters from image. Character and number images are stored in directory. The extracted text image are separated by bounding box. Each bounding box will contain each character or number. Each character or number is resized to image stored in directory. Extracted image and existing character image feature is compared. After comparison characters are detected. Finally detected characters are shown in text format. Optical character extraction is used to extract text from image. Here we will extract text from image at any lightening condition.
- Optical character extraction is used to extract text from image.
- Text will be extracted from image at any illumination condition.
- We will be using image captured by camera or webcam. Webcam images are more prone to noise and environmental interference.