Research and implementation of business English translation software based on image character recognition

Optical Character Recognition (OCR) is a technology that integrates optical and computer technologies to convert printed text into machine-readable text. The process begins with the conversion of printed characters into a binary (black and white) image, achieved by detecting the light and dark patterns of each pixel in the document. Subsequently, OCR software applies recognition algorithms to this binary image to identify and convert the characters into digital text. This digital text is then formatted into a computer-readable format, enabling further processing and editing. This technology is instrumental in digitizing printed documents, automating data entry processes, and enabling text searches in scanned documents. In the daily information office, it is often necessary to recognize valid information in text images. This paper proposes a thresholding method for text optical character information translation recognition based on OCR technology, and uses a text image thresholding image processing method based on histogram analysis and the OTSU algorithm to segment the optical character information in text images. In the segmented foreground, a thresholding optical character information translation classifier based on OCR technology is used to realize the thresholding text optical character information translation recognition. It is verified that the proposed method can achieve high accuracy and efficiency in thresholding text optical character information translation recognition, and the recognition performance of the method is remarkable compared with other recognition methods.