The research of character recognition algorithm for the automatic verification of digital instrument

Liu, Zhuofu; Luo, Zhongming; Gong, Panpan; Guo, Ming

doi:10.1109/mic.2013.6757941

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…Instrument monitoring has become a popular topic in the field of image recognition. Liu et al [30] applied image recognition technology to an automatic calibration system for gas alarm devices in underground coal mines and proposed a digital recognition algorithm. This algorithm achieves automatic verification of machine vision instruments by digitally recognising images captured by methane detectors with a recognition rate exceeding 99.9%.…”

Section: Research Statusmentioning

confidence: 99%

Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network

Hou,

Wang,

Chang

et al. 2024

Buildings

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With increasing consumption of primary energy and deterioration of the global environment, clean energy sources with large reserves, such as natural gas, have gradually gained a higher proportion of the global energy consumption structure. Monitoring and predicting consumption data play a crucial role in reducing energy waste and improving energy supply efficiency. However, owing to factors such as high monitoring device costs, safety risks associated with device installation, and low efficiency of manual meter reading, monitoring natural gas consumption data at the household level is challenging. Moreover, there is a lack of methods for predicting natural gas consumption at the household level in residential areas, which hinders the provision of accurate services to households and gas companies. Therefore, this study proposes a gas consumption monitoring method based on the K-nearest neighbours (KNN) algorithm. Using households in a residential area in Xi’an as research subjects, the feasibility of this monitoring method was validated, achieving a model recognition accuracy of 100%, indicating the applicability of the KNN algorithm for monitoring natural gas consumption data. In addition, this study proposes a framework for a natural gas consumption prediction system based on a backpropagation (BP) neural network.

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Section: Research Statusmentioning

confidence: 99%

Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network

Hou,

Wang,

Chang

et al. 2024

Buildings

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Serial number inspection for ceramic membranes via an end-to-end photometric-induced convolutional neural network framework

Cai

Deng

et al. 2021

J Intell Manuf

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Character Segmentation Method for Digital Back-Light Console Under Different Lighting Conditions

2016

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Nowadays, the amount of electronics data has been significantly increased especially for the case of capturing images. One particular application regarding this is the image capturing of the monitoring console. The real information in such console image capturing is the characters on the console. To transfer or store the captured images, a large amount of data is required. Instead of storing the whole image, some image processing techniques could be applied in order to reduce the amount of data required. In this paper, an image processing is done to the captured image by considering the value (V) parameter of the HSV (Hue, Saturation, and Value) color system. An adaptive threshold algorithm on V parameter is adopted for segmenting the console area and then the character areas from the whole image. Under different lighting conditions from 0 to 450 lux, the console area can be correctly selected. And, the characters appearing on the console area can be retrieved with 98 percent of accuracy.

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The research of character recognition algorithm for the automatic verification of digital instrument

Cited by 3 publications

References 5 publications

Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network

Natural Gas Consumption Monitoring Based on k-NN Algorithm and Consumption Prediction Framework Based on Backpropagation Neural Network

Serial number inspection for ceramic membranes via an end-to-end photometric-induced convolutional neural network framework

Character Segmentation Method for Digital Back-Light Console Under Different Lighting Conditions

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