Character energy and link energy-based text extraction in scene images
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Object reading: text recognition for object recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
A text reading algorithm for natural images
Image and Vision Computing
Multimodal alignment of scholarly documents and their presentations
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
Transform invariant text extraction
The Visual Computer: International Journal of Computer Graphics
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In this paper, we propose a new unsupervised text detection approach which is based on Histogram of Oriented Gradient and Graph Spectrum. By investigating the properties of text edges, the proposed approach first extracts text edges from an image and localize candidate character blocks using Histogram of Oriented Gradients, then Graph Spectrum is utilized to capture global relationship among candidate blocks and cluster candidate blocks into groups to generate bounding boxes of text objects in the image. The proposed method is robust to the color and size of text. ICDAR 2003 text locating dataset and video frames were used to evaluate the performance of the proposed approach. Experimental results demonstrated the validity of our approach.