Robust Angle Invariant GAS Meter Reading

In this work we propose a novel method for automatic gas meter reading from real world images. In a wide range of countries all over the world, the existing automatic technology is not adopted, usually the reading is manually done on site, and a picture is taken through a mobile device as a proof of reading. In order to confirm the reading, a tedious work of checking the proof images is commonly done offline by an operator. With this contribution we aim to supply an effective system, able to provide a real support to the validation process reducing the human effort and the time consumed. We exploit both region-based and Maximally Stable Extremal Regions techniques, during the phase involving the localization of the meter area and to detect the meter counter digits in the detection step respectively. The evaluation has been carried out on every step of our approach, as well as on the overall assessment; although the problem is complex, the proposed method leads to good results even when applied to degraded images, it represents an effective solution to the gas meter reading problem and it can be utilized in real applications.