New Fourier-Statistical Features in RGB Space for Video Text Detection

In this paper, we propose new Fourier-Statistical Features (FSF) in RGB space for detecting text in video frames of unconstrained background, different fonts, different scripts and different font sizes. This work consists of two parts namely automatic classification of text frames from a large database of text and non-text frames and FSF in RGB for text detection in the classified text frames. For text frame classification, we present novel features based on three visual cues, namely, sharpness in filter-edge maps, straightness of the edges and proximity of the edges to identify a true text frame. For text detection in video frames, we present new Fourier transform based features in RGB space with statistical features and the computed FSF features from RGB bands are subject to K-means clustering to classify text pixels from the background of the frame. Text blocks of the classified text pixels are determined by analyzing the projection profiles. Finally, we introduce a few heuristics t...

• Type: Journal
• Year: 2010
• Where: TCSV
• Authors: Palaiahnakote Shivakumara, Trung Quy Phan, Chew Lim Tan
• Keywords: Classified Text, Computational Biology, TCSV 2010, Text Detection, Text Frame