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This paper proposes the use of a new symmetry property based on proximity of the median moments in the wavelet domain. The method divides a given frame into 16 equally sized blocks to classify the true text frame. The average of high frequency subbands of a block is used for computing median moments to brighten the text pixel in a block of video frame. Then K-means clustering with K=2 is applied on...
Text frame classification is needed in many applications such as event identification, exact event boundary identification, navigation, video surveillance in multimedia etc. To the best of our knowledge, there are no methods reported solely dedicated to text frame classifications so far. Hence this paper presents a new approach to text frame classification in video based on capturing local observable...
In this paper, we propose a new method based on wavelet transform, statistical features and central moments for both graphics and scene text detection in video images. The method uses wavelet single level decomposition LH, HL and HH subbands for computing features and the computed features are fed to k means clustering to classify the text pixel from the background of the image. The average of wavelet...
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