scholarly journals Detection of Inclement Weather Conditions at a Signalized Intersection using a Video Image Processing Algorithm

2006 ◽  
Author(s):  
Anuj Sharma ◽  
Darcy Bullock ◽  
Srinivas Peeta ◽  
James Krogmeier
Keyword(s):  
Image Processing ◽  
Weather Conditions ◽  
Video Image ◽  
Signalized Intersection ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Inclement Weather ◽  
Video Image Processing

Design of DSP Video Image Processing System Control Software

2010 ◽  
Vol 139-141 ◽  
pp. 2299-2302
Author(s):  
Hong Yuan Wen
Keyword(s):  
Image Processing ◽  
Processing System ◽  
Video Image ◽  
System Control ◽  
Image Processing Algorithm ◽  
Control Software ◽  
Ultra Low Power ◽  
Image Processing System ◽  
Protection Circuit ◽  
Video Image Processing

In order to realize the DSP Video Image Processing System works well in the highlight environment, the system control software is designed. In this control part, the ultra-low power MSP430 single chip microcomputer (MCU) is the core, which can be programmed to control the DSP Video Image Processing System, the video A/D converter and the highlight protection circuit by the Inter-Integrated Circuit (I2C) bus. The Image Processing algorithm models can be selected. Whether the highlight protection circuit is turned on or not depends on the comparison result of the environment light and the MCU light threshold. The control program code has been debugged and tested through the MSP development board and the IAR C-SPY debugger. The result shows the DSP Video Image Processing System Control Software is ideal.

Traffic incident detection system based on video image processing

2008 ◽  
Vol 28 (7) ◽  
pp. 1886-1889 ◽  
Author(s):  
Qin WANG ◽  
Shan HUANG ◽  
Hong-bin ZHANG ◽  
Quan YANG ◽  
Jian-jun ZHANG
Keyword(s):  
Image Processing ◽  
Detection System ◽  
Video Image ◽  
Incident Detection ◽  
Traffic Incident ◽  
Video Image Processing

Internal quality evaluation of chestnut using nuclear magnetic resonance

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Soo Hyun Park ◽  
Sang Ha Noh ◽  
Michael J. McCarthy ◽  
Seong Min Kim
Keyword(s):  
Image Processing ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Processing Algorithm ◽  
Internal Quality ◽  
Soluble Solid Content ◽  
Mr Images ◽  
Image Processing Algorithm ◽  
Internal Defects ◽  
Nuclear Magnetic

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

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