This paper describes a semi-automatic tool for annotation of multi-script text from natural scene images. The procedure involves manual seed selection followed by a region growing process to segment each word present in the image. The threshold for region growing can be varied by the user so as to ensure pixel-accurate character segmentation. The text present in the image is tagged word-by-word. A virtual keyboard interface has also been designed for entering the ground truth in ten Indic scripts, besides English. The keyboard interface can easily be generated for any script, thereby expanding the scope of the toolkit. Optionally, each segmented word can further be labeled into its constituent characters/symbols. Polygonal masks are used to split or merge the segmented words into valid characters/symbols. The ground truth is represented by a pixel-level segmented image and a ‘.txt’ file that contains information about the number of words in the image, word bounding boxes, script and ground truth Unicode. The toolkit can be used to generate ground truth and annotation for any generic document image and hence is useful for researchers in the document image processing community for evaluating the performance of document analysis and recognition techniques.
Added on August 13, 2014
Product Type : Research Paper
License Type : Freeware
System Requirement :
Author : T Kasar, D Kumar, D Girish, A G Ramakrishnan