2020/10/31 by Shuonan Pei, Pei, Shuonan, Mingzhi Zhu +1
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Image and Object Detection Techniques #Vehicle License Plate Recognition #cs.CV
paper · pdf · doi:10.48550/arxiv.2011.00380
arxiv created 2020/10/31 · openalex publication_date 2020/10/31 · arxiv updated 2020/11/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Inrecentyears,ConvolutionalNeuralNet-work(CNN) is quite a popular topic, as it is a powerful andintelligent technique that can be applied in various fields.The YOLO is a technique that uses the algorithms for real-time text detection tasks. However, issues like, photometricdistortion and geometric distortion, could affect the systemYOLO accuracy and cause system failure. Therefore, thereare improvements that can make the system work better. Inthis paper, we are going to present our solution - a potentialsolution of a fast and accurate real-time text direction andrecognition system. The paper covers the topic of Real-TimeText detection and recognition in three major areas: 1. videoand image preprocess, 2. Text detection, 3. Text recognition. Asa mature technique, there are many existing methods that canpotentially improve the solution. We will go through some ofthose existing methods in the literature review session. In thisway, we are presenting an industrial strength, high-accuracy,Real-Time Text Detection and recognition tool.