scholarly journals Research on Applications of Image Processing Technologies in Intelligent Transportation

2018 ◽  
Author(s):  
Tinghui Ye
Keyword(s):  
Image Processing ◽  
Intelligent Transportation ◽  
Processing Technologies

A Hair Volume Analysis System Using Deep Learning and Image Processing Technologies

2021 ◽  
Author(s):  
Ming-Che Chen ◽  
Wan-Jung Chang ◽  
Yu-Xiang Xiao ◽  
Zi-Xuan Zhang ◽  
Yi-Chan Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Processing Technologies ◽  
Volume Analysis ◽  
Analysis System

Vehicle Security Distance Control Based on Binocular Parallax Vision

2014 ◽  
Vol 644-650 ◽  
pp. 207-210
Author(s):  
Shuang Liu ◽  
Xiang Jie Kong ◽  
Ming Cai Shan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
High Precision ◽  
Stereo Matching ◽  
Vision System ◽  
Intelligent Transportation ◽  
Distance Control ◽  
Calibration Methods ◽  
Computer Vision Technology ◽  
Vehicle Security

Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

Study on Soil Particle Size Distribution by Digital Image Processing

2013 ◽  
Vol 788 ◽  
pp. 627-630
Author(s):  
Jian Shu Hou
Keyword(s):  
Mechanical Property ◽  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image ◽  
Traditional Method ◽  
Processing Method ◽  
Distribution Analysis ◽  
Processing Technologies

The particle size distribution of soil is very importantto its physical and mechanical property. The ordinary method of the particlesize distribution analysis is based on shaking the soil through a set of sieves.But it will be difficult to use the method while there have particles largerthan the biggest aperture of the size sieves. Then the digital image processingwas used to solve the problem here. The processing technologies, such as imageanalysis and enhancement, deblurring, edge detection were studied to analyzethe image of soil particles. Then the image processing method was used to getthe particle size distribution accurately. Though some promotions need to becarried out in the further study, it is can be found that the image processingmethod is more efficiently than the traditional method.

scholarly journals Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled

2020 ◽  
Vol 10 (19) ◽  
pp. 7005
Author(s):  
Che-Ming Chang ◽  
Chern-Sheng Lin ◽  
Wei-Cheng Chen ◽  
Chung-Ting Chen ◽  
Yu-Liang Hsu
Keyword(s):  
Image Processing ◽  
Skin Color ◽  
Digital Camera ◽  
Human Machine Interface ◽  
Head Motion ◽  
Processing Technologies ◽  
Color Recognition ◽  
Machine Interface ◽  
Head Control ◽  
Head Gestures

The human–machine interface with head control can be applied in many domains. This technology has the valuable application of helping people who cannot use their hands, enabling them to use a computer or speak. This study combines several image processing and computer vision technologies, a digital camera, and software to develop the following system: image processing technologies are adopted to capture the features of head motion; the recognized head gestures include forward, upward, downward, leftward, rightward, right-upper, right-lower, left-upper, and left-lower; corresponding sound modules are used so that patients can communicate with others through a phonetic system and numeric tables. Innovative skin color recognition technology can obtain head features in images. The barycenter of pixels in the feature area is then quickly calculated, and the offset of the barycenter is observed to judge the direction of head motion. This architecture can substantially reduce the distraction of non-targeted objects and enhance the accuracy of systematic judgment.

AUTOMATED CLASSIFICATION OF BREAST CARCINOMA CELL BASED ON IMAGE PROCESSING AND SUPPORT VECTOR MACHINE

2010 ◽  
Vol 22 (02) ◽  
pp. 127-135 ◽  
Author(s):  
Yung-Lung Kuo ◽  
Chien-Chuan Ko ◽  
Yueh-Min Lin ◽  
Yong-Min Chen
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Breast Cancer Diagnosis ◽  
Support Vector ◽  
Automated Classification ◽  
Processing Technologies ◽  
Major Health ◽  
Suitable Treatment ◽  
Breast Tissues

As breast cancer is a substantial threat to the lives of women, it has become a major health issue in the world over the past 50 years, and its incidence has increased in the recent years. Early diagnosis and suitable treatment is relatively important. In the process of breast screening, tissue biopsy is an important operation in determining the presence of breast cancer. It not only provides an accurate diagnosis of the disease but also determines the prognosis for breast cancer. The main goal of this study is to develop a breast cancer diagnosis system based on histopathology and a sequence of image-processing technologies to analyze H&E stained images of breast tissues. The proposed system can automatically detect the mitosis of nuclei and analyze the size and the shape of nuclei to evaluate the duct structure of the breast tissue. Moreover, it provides physicians quantitative prognosis and classification of tissue malignancy, which will improve the diagnostic accuracy and efficiency of the cancer.

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