Research on Image Processing Algorithm in Intelligent Vehicle System Based on Visual Navigation

2019 ◽  
pp. 1678-1688
Author(s):  
Congbo Luo ◽  
Zihe Tong
Keyword(s):  
Image Processing ◽  
Visual Navigation ◽  
Processing Algorithm ◽  
Intelligent Vehicle ◽  
Image Processing Algorithm ◽  
Vehicle System

Design of an Intelligent Vehicle System for Storehouse Management Based on Image Processing and RFID Technologies

2011 ◽  
Vol 201-203 ◽  
pp. 2007-2013 ◽  
Author(s):  
Wen Dong Li ◽  
Guo Wei Chen ◽  
Jing Chen ◽  
Xue Jun Zhang
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Radio Frequency Identification ◽  
High Accuracy ◽  
Visual Navigation ◽  
Intelligent Vehicle ◽  
Vehicle System ◽  
Logistics Enterprises ◽  
Frequency Identification ◽  
Straight Lines

This paper describes a new intelligent storehouse management vehicle system based on image processing and Radio Frequency Identification (RFID) technologies to ensure the security of storehouses of logistics enterprises and improve the efficiency of storage. The vehicle is able to go ahead automatically by visual navigation in storehouses with the function of face recognition and alarm, as well as automatic statistics of commodities. Hough transformation is used to detect straight lines for angle control, and RFID based component is applied to the commodity management. The results show that our vehicle and storehouse management system can successfully fulfill various tasks with high accuracy of performance, which will lead to a practical merchandise application after further improvements.

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.

An Image Processing Algorithm to Find New and Old Bruises

1995 ◽  
Vol 11 (5) ◽  
pp. 751-757 ◽  
Author(s):  
J. A. Throop ◽  
D. J. Aneshansley ◽  
B. L. Upchurch
Keyword(s):  
Image Processing ◽  
Processing Algorithm ◽  
Image Processing Algorithm

scholarly journals Image Processing Algorithm for Weight Estimation of Dairy Cattle

2011 ◽  
Vol 36 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Kwang-Wook Seo ◽  
Hyeon-Tae Kim ◽  
Dae-Weon Lee ◽  
Yong-Cheol Yoon ◽  
Dong-Yoon Choi
Keyword(s):  
Image Processing ◽  
Dairy Cattle ◽  
Processing Algorithm ◽  
Weight Estimation ◽  
Image Processing Algorithm
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