• Naga Sudha
• Y.Madhavee Latha

Scene text detection from video as well as natural scene images is challenging due to the variations in background, contrast, text type, font type, font size, and so on. Besides, arbitrary orientations of texts with multi-scripts add more complexity to the problem. The proposed approach introduces a new idea of convolving Laplacian with wavelet sub-bands at different levels in the frequency domain for enhancing low resolution text pixels. Then, the results obtained from different sub-bands (spectral) are fused for detecting candidate text pixels. We explore maxima stable extreme regions along with stroke width transform for detecting candidate text regions. Text alignment is done based on the distance between the nearest neighbour clusters of candidate text regions. In addition, the approach presents a new symmetry driven nearest neighbour for restoring full text lines.

Text detection, character recognition, text extraction, scene image,text alignment,stroke width transform.

"MULTI-SPECTRAL FUSION BASED SCENE TEXT DETECTION IN VIDEO IMAGES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.293-297, January-2019, Available :http://www.jetir.org/papers/JETIR1901940.pdf

"MULTI-SPECTRAL FUSION BASED SCENE TEXT DETECTION IN VIDEO IMAGES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp293-297, January-2019, Available at : http://www.jetir.org/papers/JETIR1901940.pdf