A New Fourier-Moments Based Video Word and Character Extraction Method for Recognition

— This paper presents a new method based on Fourier and moments features to extract words and characters from a video text line in any direction for recognition. Unlike existing methods which output the entire text line to the ensuing recognition algorithm, the proposed method obtains each extracted character from the text line as input to the recognition algorithm because the background of a single character is relatively simple compared to the text line and words. Max-Min clustering criterion is introduced to obtain text cluster from the extracted Fourier and moments feature set. Union of the text cluster with Canny operation of the input video text line is proposed to obtain missing text candidates. Then a run length criterion is used for extraction of words. From the words, we propose a new idea for extracting characters from the text candidates of each word image based on the fact that the text height difference at the character boundary column is smaller than that at other colu...

• Type: Journal
• Year: 2011
• Where: ICDAR
• Authors: Deepak Rajendran, Palaiahnakote Shivakumara, Bolan Su, Shijian Lu, Chew Lim Tan
• Keywords: Document Analysis, ICDAR 2011, Recognition Algorithm, Word Image, Word Segmentation