scholarly journals High-speed Keyboard Inspection System with Self-learning Algorithm, using Camera Type High Resolution Image Scanner

1988 ◽  
Vol 108 (5) ◽  
pp. 339-346
Author(s):  
Tetsuo Koezuka ◽  
Noriyuki Hiraoka ◽  
Masato Nakashima ◽  
Takefumi Inagaki
Author(s):  
Zichong Chen ◽  
Xianwen Luo

Aiming at the problem of low baud rate of traditional high-resolution image synchronous acquisition fuzzy control method, a high-resolution image synchronous acquisition fuzzy control method based on machine learning is designed. By detecting the fuzzy edge information of high-resolution image, the fuzzy membership function of synchronous acquisition quantity is proposed, and the gradient amplitude of synchronous acquisition quantity of high-resolution image is calculated. The unsupervised learning algorithm based on machine learning is used to cluster the fuzzy control data, so as to determine the fuzzy space of synchronous acquisition quantity of high-resolution image, and calculate the fuzzy feature similarity, the fuzzy control of synchronous acquisition quantity of high resolution image is realized. Experimental results show that the controlled wave rate in this paper solves the problem of low wave rate in 255.63 bps/h-271.33 bps/h, and significantly improves the control accuracy.


2010 ◽  
Vol 44-47 ◽  
pp. 3859-3863
Author(s):  
Kai Hua Wu ◽  
Jian Xin Fan

Measurement of wheel set wear was an important step for the safety of train running. High-speed acquisition and processing method for high resolution image of wheel set based on the hardware platform of DSP (digital signal processor) and PC was proposed. High-speed acquisition and processing was completed by PC and DSP unit separately. PC and DSP unit worked in parallel operational mode. Ethernet transport program based on TCP was designed for data exchange. Asynchronous reset pulse generation circuits were designed. High resolution images of wheel set were captured in 500fps and asynchronous reset mode. Resolution of images was 1280*1024. The experimental results showed that this method improved image processing speed effectively.


Author(s):  
Seunghyeok Shin ◽  
Jongmin Lee ◽  
Sangwook Lee ◽  
Taeseok Yang ◽  
Whoi-Yul Kim

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