Title :
Recognition of the numbers of numerical civilian instrumentations based on bp neural network
Author :
Bai, Qiushi ; Zhang, Yunzhou ; Tan, Jiyuan ; Zhao, Limeng ; Qi, Zixin
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
With the rapid development of intelligent building, the requirement of automatic number identification of civilian instrumentations is increasingly urgent. This article uses iterative global threshold to binarize the images and then adopts projection method to locate the target regions and divide the numbers. The back-propagation neural network is used to recognize the numbers. The result indicates that the recognition rate is above 98%.
Keywords :
backpropagation; computerised instrumentation; image recognition; image segmentation; neural nets; automatic number identification; back-propagation neural network; intelligent building; iterative global threshold; numerical civilian instrumentations; projection method; Character recognition; Gray-scale; Histograms; Image recognition; Instruments; Intelligent structures; Iterative methods; Neural networks; Pattern recognition; Pixel; BP; civilian instrumentation; neural network; number recognition;
Conference_Titel :
Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3817-4
DOI :
10.1109/ICIMA.2009.5156571
