Research on image text recognition based on canny edge detection algorithm and k-means algorithm

• DOI: 10.1007/s13198-021-01262-0
• Publication Date: 2021-08-22T06:02:34Z
• Authors: Fangsheng Wu; Changan Zhu; Jinxiu Xu; Mohammed Wasim Bhatt; Ashutosh Sharma
• Keywords: Canny edge detector; Recall rate; Optical character recognition

The latest research in the field of recognition of image characters has led to various developments in the modern technological works for the improvement of recognition rate and precision. This technology is significant in the field of character recognition, business card recognition, document recognition, vehicle license plate recognition etc. for smart city planning, thus its effectiveness should be improved. In order to improve the accuracy of image text recognition effectively, this article uses canny algorithm to process edge detection of text, and k-means algorithm for cluster pixel recognition. This unique combination combined with maximally stable extremal region and optimization of stroke width for image text yields better results in terms of recognition rate, recall, precision, F-score and accuracy. The results show that the correct recognition rate is 88.3% and 72.4% respectively with an accuracy value of 90.5% for the proposed method. This algorithm has high image text recognition rate, can recognize images taken in complex environment, and has good noise removal function. It is significantly an optimal algorithm for image text recognition.