吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (01): 250-255.

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Text localization algorithm in complex scene based on corner-type feature and histogram of oriented gradients of edge magnitude statistical feature

JIANG Wei, LU Zhao-yang, LI Jing, LIU Xiao-pei   

  1. State Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China
  • Received:2011-12-14 Online:2013-01-01 Published:2013-01-01

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Abstract: The corner-type feature based on photometric invariants and the Histogram of Oriented Gradients of Edge Magnitude (HOG-EM) statistical feature are proposed to overcome the interference of the texture-rich non-text regions to the text localization algorithm. A two-stage multilayer text localization algorithm in complex scene is presented on the basis of the two novel features. In the proposed method, first, edge map is obtained and eight layers of binary maps in the Hue Saturation and Lightness (HSL) space are generated according to the characteristics of the HSL space. Then, nine layers of sub-maps are formed to gain text candidate blocks with multilayer connected component analysis. Finally, the two novel features mentioned above are extracted to remove the non-text block from the text candidate blocks and keep the text. Experiments indicate that the proposed scheme can efficiently remove non-text texture-rich regions, decrease false-alarm rate and obtain reasonable accuracy and recall rate.

Key words: information processing technology, text localization, corner-type, histogram of oriented gradients, photometric invariants

CLC Number: 

  • TN911.72
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