An ELM Based Barcode Localization Algorithm

Chun Cai Wang; Ying Tao Li; Yu Dong Yang

doi:10.4028/www.scientific.net/AMM.380-384.1185

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384An ELM Based Barcode Localization Algorithm

An ELM Based Barcode Localization Algorithm

Abstract:

Many applications have provided functions of automatic searching and reading barcodes in complex scenes with a camera. However state of the art barcode detection systems are limited to their serious requirement, such as shooting angle, light intensity and revolution. This paper proposes an effective solution for automatic barcode localization by exploiting ELM (extreme learning machine) and multichannel Gabor filtering techniques. We first employ Gabor filter to extract texture feature of the barcode, and then the barcode regions and the background region in texture image are use to train the ELM classifier. Finally, we apply our method to the barcode image database, which consists of several different barcode symbologies. Experiment shows our method is superior to the General morphology method and has desirable properties in accuracy, rotation invariance and robustness to noise.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

1185-1188

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.1185

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Online since:

August 2013

Authors:

Chun Cai Wang, Ying Tao Li, Yu Dong Yang

Keywords:

Barcode, Extreme Learning Machine (ELM), Gabor Filter, Localization, Texture

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