A skeleton-based method for multi-oriented video text detection

In this paper, we propose a method based on the skeletonization operation for multi-oriented video text detection. The first step uses our existing Laplacian-based method to identify candidate text regions. In the second step, each region is classified as either a simple connected component (a single text string) or a complex connected component (multiple text strings that are connected to each other) depending on the number of intersection points in its skeleton. Complex connected components are then segmented into constituent parts based on the skeleton segments in order to separate the text strings from each other. Finally, text string straightness and edge density are used for false positive elimination. Experimental results show that the proposed method is able to detect multi-oriented graphics text and scene text. Categories and Subject Descriptors I.4.6 [Image Processing and Computer Vision]: Segmentation

• Type: Conference
• Year: 2010
• Where: DAS
• Authors: Trung Quy Phan, Palaiahnakote Shivakumara, Chew Lim Tan
• Keywords: Complex Connected Components, Connected Component, DAS 2010, Document Analysis, Video Text Detection