A Robust Algorithm for Text String Separation from Mixed Text/Graphics Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Methods for Ridge and Valley Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multilocal creaseness based on the level-set extrinsic curvature
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
A Rotation Invariant Rule-Based Thinning Algorithm for Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Text/Graphics Separation in Maps
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
Text/Graphics Separation Revisited
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Color segmentation for text extraction
International Journal on Document Analysis and Recognition
Extraction and recognition of geographical features from paper maps
International Journal on Document Analysis and Recognition
Topological Histogram Reduction Towards Colour Segmentation
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Automatic watershed segmentation of randomly textured color images
IEEE Transactions on Image Processing
Document seal detection using GHT and character proximity graphs
Pattern Recognition
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Automatic separation of text and symbols from graphics in document image is one of the fundamental aims in graphics recognition. In maps, separation of text and symbols from graphics involves many challenges because the text and symbols frequently touch/overlap with graphical components. Sometimes the colors in a single character are gradually distributed which adds extra difficulty in text and symbol separation from color maps. In this paper we proposed a system to retrieve text and symbol from color map. Here, at first, we separate the map into different foreground layers according to color features and then in each layer, connected component features and skeleton information are used to identify text and symbol from graphics on the basis of their geometrical features. Lastly, segmentation results of the individual layers are combined to get final segmentation results. From the experiment we obtained encouraging results.