Based on Improved Edge Detection Algorithm for English Text Extraction and Restoration From Color Images

The superimposed text in color images is an important clue to help understand the content of the image. Extracting and translating it into a familiar language is a hot research topic in the current image field. However, because the background of the image is usually complicated, effective text extraction and restoration is very challenging. In view of the above problems, this paper proposes an English text repair and extraction algorithm for color images based on improved edge detection algorithm. Firstly, the text of the color image is repaired by the sample block-based method. Secondly, the traditional edge-based detection method is improved, and the image is grayed out, and the edge detection is performed to obtain the candidate text area. Then, using the restrictive conditions such as text color and size, the text area is filtered out to extract the target text. Finally, the text information embedded in the extracted processed color image is translated into the target language. The experimental results show that the proposed algorithm has higher accuracy and faster computing speed, and achieves a better comprehensive effect. It further illustrates the extraction of English text by image processing technology, which can facilitate machine translation.