GAS meter reading from real world images using a multi-net system

作     者：Vanetti, Marco Gallo, Ignazio Nodari, Angelo 

作者机构：Univ Insubria Dipartimento Sci Teor & Appl I-21100 Varese Va Italy 

出 版 物：《PATTERN RECOGNITION LETTERS》 (模式识别快报)

年 卷 期：2013年第34卷第5期

页      面：519-526页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Object detection Object segmentation Text localization Ocr Neural networks Multi-net system 

摘      要：We present a new approach for automatic gas meter reading from real world images. The gas meter reading is usually done on site by an operator and a picture is taken from a mobile device as proof of reading. Since the reading operation is prone to errors, the proof image is checked offline by another operator to confirm the reading. In this study, we present a method to support the validation process in order to reduce the human effort. Our approach is trained to detect and recognize the text of a particular area of interest. Firstly we detect the region of interest and segment the text contained using a method based on an ensemble of neural models. Then we perform an optical character recognition using a Support Vector Machine. We evaluated every step of our approach, as well as the overall assessment, showing that despite the complexity of the problem our method provide good results also when applied to degraded images and can therefore be used in real applications. (C) 2012 Elsevier B.V. All rights reserved.