@conference {Elaalyani2017,
	title = {Current trends in text-spotting},
	booktitle = {Proceedings - 2017 International Conference on Wireless Networks and Mobile Communications, WINCOM 2017},
	year = {2017},
	note = {cited By 0},
	abstract = {Text spotting, i.e., the localization and recognition of text occurrences in natural images and videos, is a challenging problem in computer vision. Important applications of text spotting are: video indexing, retrieval and search, the support of blind persons in finding their way in unknown environments and reading street and shop signs for autonomously driving vehicles or car license plate recognition in traffic control systems. Recently, the use of deep convolutional neural networks as well as recognizing whole words instead of single characters led to significant progress in the field of text spotting. Furthermore, there is a tendency towards merging and unifying the single steps of the text spotting pipeline. Despite current progress, it is still difficult to recognize in-scene text in comparison to overlaid text. This work gives an overview of the state-of-the-art in text spotting and highlights current breakthroughs and trends. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/WINCOM.2017.8238215},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041435238\&doi=10.1109\%2fWINCOM.2017.8238215\&partnerID=40\&md5=a2aecbf47ec51f3f316606d512724a5a},
	author = {Elaalyani, I. and Erradi, M. and M{\"u}hling, M. and Freisleben, B.}
}
