Title :
Unsupervised text extraction from G-maps
Author :
Adak, Chandranath
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Kalyani, Kalyani, India
Abstract :
This paper represents an text extraction method from Google maps, GIS maps/images. Due to an unsupervised approach there is no requirement of any prior knowledge or training set about the textual and non-textual parts. Fuzzy C-Means clustering technique is used for image segmentation and Prewitt method is used to detect the edges. Connected component analysis and gridding technique enhance the correctness of the results. The proposed method reaches 98.5% accuracy level on the basis of experimental data sets.
Keywords :
document image processing; edge detection; fuzzy set theory; image segmentation; pattern clustering; text detection; unsupervised learning; G-maps; GIS maps; Google maps; Prewitt method; connected component analysis; edge detection; fuzzy C-means clustering; gridding technique; image segmentation; unsupervised text extraction; Accuracy; Data mining; Google; Graphics; Image edge detection; Image segmentation; Fuzzy C-Means clustering; clustering; connected component; gridding; text extraction;
Conference_Titel :
Human Computer Interactions (ICHCI), 2013 International Conference on
Conference_Location :
Chennai
DOI :
10.1109/ICHCI-IEEE.2013.6887782
