M
Michael Blumenstein
Researcher at University of Technology, Sydney
Publications - 343
Citations - 5826
Michael Blumenstein is an academic researcher from University of Technology, Sydney. The author has contributed to research in topics: Feature extraction & Handwriting recognition. The author has an hindex of 37, co-authored 328 publications receiving 4764 citations. Previous affiliations of Michael Blumenstein include Commonwealth Scientific and Industrial Research Organisation & Australian Artificial Intelligence Institute.
Papers
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Proceedings Article
Improving the Segmentation of Cursive Handwritten Words using Ligature Detection and Neural Validation
TL;DR: An enhanced neural network-based segmentation technique for improving the segmentation process in cursive handwriting recognition and is implemented and tested on a benchmark database providing encouraging results.
Proceedings ArticleDOI
Gradient-Angular-Features for Word-wise Video Script Identification
TL;DR: This paper presents new Gradient-Angular-Features (GAF) for video script identification, namely, Arabic, Chinese, English, Japanese, Korean and Tamil, and proposes novel GAF for the PTC to study the structure of the components in the form of cursiveness and softness.
Journal ArticleDOI
Fractals based multi-oriented text detection system for recognition in mobile video images
Palaiahnakote Shivakumara,Liang Wu,Tong Lu,Chew Lim Tan,Michael Blumenstein,Basavaraj S. Anami +5 more
TL;DR: This work introduces fractals for text detection in video captured by mobile cameras in a novel way in the gradient domain and proposes to use k-means clustering for separating text components from non-text ones and direction guided boundary growing is proposed to extract multi-oriented texts.
Journal ArticleDOI
Prediction of maximum wave-induced liquefaction in porous seabed using multi-artificial neural network model
TL;DR: In this paper, a data dependent approach for the prediction of the wave-induced liquefaction depth in a porous seabed is proposed, based on a multi-artificial neural network (MANN) method.
Journal ArticleDOI
Arbitrarily-oriented multi-lingual text detection in video
TL;DR: A novel idea for determining automatic windows to extract moments for tackling multi-font and multi-sized text in video based on stroke width information is introduced and outperforms the state-of-the-art methods.