Research on English Character Recognition Technology Based on OCR

To enhance the efficiency of English intelligent translation in image processing, we have designed and implemented an English translation system based on Optical Character Recognition (OCR) technology. In this system, we use the OTSU algorithm for image binarization, converting the image into a binary color of black and white, which simplifies character recognition. Additionally, to improve image quality and reduce noise interference, we combine the use of median filter and Gaussian filter techniques for image denoising. during the character recognition phase, we employ opencv-python for image processing, which is capable of accurately identifying various types of text. By utilizing the Python programming language and the pycharm tool, we enable Python programs to easily call opencv for character recognition. Through this series of processing, we enable the system to effectively recognize English characters in images. validate the effectiveness of the system, we conduct systematic recognition tests on the processed images. The results show that the images, processed with image preprocessing and the opencv-python module and then subjected to OCR processing, allow the system to accurately recognize English characters in the images, with a high accuracy rate. This result indicates that our English translation system exhibits high accuracy and efficiency in image recognition.