Muhammad Imran^1,*, Hafeez Anwar², Muhammad Tufail¹, Abdullah Khan¹, Murad Khan³, Dzati Athiar Ramli⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 203-216, 2023, DOI:10.32604/cmc.2023.029834

Abstract We propose to perform an image-based framework for electrical energy meter reading. Our aim is to extract the image region that depicts the digits and then recognize them to record the consumed units. Combining the readings of serial numbers and energy meter units, an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time setup. However, such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display, orientation and scale variations caused by camera positioning, and… More >

Ji Wang¹, Liming Li^1,2,3, Shubin Zheng^1,3, Shuguang Zhao², Xiaodong Chai^1,3, Lele Peng^1,3, Weiwei Qi^1,3, Qianqian Tong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1671-1706, 2023, DOI:10.32604/cmes.2022.022143

Abstract Loosening detection; cascade deep convolutional neural network; object localization; saliency detection problem of bolts on axlebox covers. Firstly, an SSD network based on ResNet50 and CBAM module by improving bolt image features is proposed for locating bolts on axlebox covers. And then, the A²-PFN is proposed according to the slender features of the marker lines for extracting more accurate marker lines regions of the bolts. Finally, a rectangular approximation method is proposed to regularize the marker line regions as a way to calculate the angle of the marker line and plot all the angle values into an angle table, according… More > Graphic Abstract