A novel mutual nearest neighbor based symmetry for text frame classification in video

In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection etc. We propose a new text frame classification method that introduces a combination of wavelet and median-moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max-Min Clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called Mutual Nearest Neighbor based Symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created...

• Type: Journal
• Year: 2011
• Where: PR
• Authors: Palaiahnakote Shivakumara, Anjan Dutta, Trung Quy Phan, Chew Lim Tan, Umapada Pal
• Keywords: Distributed And Parallel Computing, Feature Combination, Frame Levels, PR 2011, Public Datasets