Efficient visual code localization with neural networks

The use of computer-readable visual codes became common in our everyday life both in industrial environments and for private use. The reading process of visual codes consists of two steps, namely, localization and data decoding. In this paper we examine the localization step of visual codes usin...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Bodnár Péter
Grósz Tamás
Tóth László
Nyúl László Gábor
Dokumentumtípus: Cikk
Megjelent: 2018
Sorozat:PATTERN ANALYSIS AND APPLICATIONS 21 No. 1
doi:10.1007/s10044-017-0619-6

mtmt:3210082
Online Access:http://publicatio.bibl.u-szeged.hu/20911
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520 3 |a The use of computer-readable visual codes became common in our everyday life both in industrial environments and for private use. The reading process of visual codes consists of two steps, namely, localization and data decoding. In this paper we examine the localization step of visual codes using conventional and deep rectifier neural networks. They are also evaluated in the discrete cosine transform domain and shown to be efficient, which makes full decompression unnecessary for setups involving JPEG images. This approach is also efficient from a storage viewpoint and computation cost viewpoint, since camera hardware can provide a JPEG stream as output in many cases. The use of neural networks implemented on graphics processing unit allows real-time automatic code object localization. In our earlier studies, the proposed approach was evaluated on the most popular code type, quick response code, and some other 2D codes as well. Here, we also prove that deep rectifier networks are also suitable for 1D barcode localization and present extensive evaluation and comparison to state-of-the-art approaches. 
700 0 1 |a Grósz Tamás  |e aut 
700 0 1 |a Tóth László  |e aut 
700 0 1 |a Nyúl László Gábor  |e aut 
856 4 0 |u http://publicatio.bibl.u-szeged.hu/20911/1/Bodnar2018_Article_EfficientVisualCodeLocalizatio.pdf  |z Dokumentum-elérés