TY - GEN
T1 - An algorithm for colour-based natural scene text segmentation
AU - Zeng, Chao
AU - Jia, Wenjing
AU - He, Xiangjian
PY - 2012
Y1 - 2012
N2 - Before the step for text recognition, a text image needs to be segmented into foreground containing only the text area and background. In this paper, a method is proposed for segmenting colour natural scene texts which suffer from a wide range of degradations with complex background. A text image is firstly processed by two 3-means clustering operations with different distance measurements. Then, a modified connected component (CC)-based validation method is used to obtain the text area after clustering. Thirdly, a proposed objective segmentation evaluation method is utilised to choose the final segmentation result from the two segmented text images. The proposed method is compared with other existing methods based on the ICDAR2003 public database. Experimental results show the effectiveness of the proposed method.
AB - Before the step for text recognition, a text image needs to be segmented into foreground containing only the text area and background. In this paper, a method is proposed for segmenting colour natural scene texts which suffer from a wide range of degradations with complex background. A text image is firstly processed by two 3-means clustering operations with different distance measurements. Then, a modified connected component (CC)-based validation method is used to obtain the text area after clustering. Thirdly, a proposed objective segmentation evaluation method is utilised to choose the final segmentation result from the two segmented text images. The proposed method is compared with other existing methods based on the ICDAR2003 public database. Experimental results show the effectiveness of the proposed method.
KW - connected component analysis (CCA)
KW - k-means clustering
KW - natural scene text segmentation
KW - segmentation evaluation
UR - http://www.scopus.com/inward/record.url?scp=84860811713&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-29364-1_5
DO - 10.1007/978-3-642-29364-1_5
M3 - Conference contribution
AN - SCOPUS:84860811713
SN - 9783642293634
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 58
EP - 68
BT - Camera-Based Document Analysis and Recognition - 4th International Workshop, CBDAR 2011, Revised Selected Papers
T2 - 4th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2011
Y2 - 22 September 2011 through 22 September 2011
ER -