Frontiers of Image Processing Technologies and Applications. Inteligent Video Analysis and Its Application.

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.

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Embedded Image Processing and Video Analysis in Intelligent Camera-based Vision System

2020 9th Mediterranean Conference on Embedded Computing (MECO) ◽

10.1109/meco49872.2020.9134254 ◽

2020 ◽

Author(s):

Boris A. Alpatov ◽

Pavel V. Babayan ◽

Maksim D. Ershov

Keyword(s):

Image Processing ◽

Video Analysis ◽

Vision System ◽

Embedded Image Processing ◽

Embedded Image

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

Applied Sciences ◽

10.3390/app10197005 ◽

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.

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Image processing technologies in intelligent transportation systems

10.1117/12.539002 ◽

2003 ◽

Cited By ~ 1

Author(s):

Zhengyou Wang ◽

Jilin Liu

Keyword(s):

Image Processing ◽

Intelligent Transportation Systems ◽

Intelligent Transportation ◽

Transportation Systems ◽

Processing Technologies

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

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237210001840 ◽

2010 ◽

Vol 22 (02) ◽

pp. 127-135 ◽

Cited By ~ 4

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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Processing of Images and Videos for Extracting Text Information from Clustered Features Using Graph Wavelet Transform

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2019.7768 ◽

2019 ◽

Vol 16 (2) ◽

pp. 557-561

Author(s):

Merlin L. M. Livingston ◽

Agnel L. G. X. Livingston

Keyword(s):

Image Processing ◽

Wavelet Transform ◽

Video Analysis ◽

Hill Climbing ◽

Primary Role ◽

Hill Climbing Algorithm ◽

Meaningful Information ◽

Spectral Graph ◽

Text Information ◽

Sensitivity Specificity

Image processing is an interesting domain for extracting knowledge from real time video and images for surveillance, automation, robotics, medical and entertainment industries. The data obtained from videos and images are continuous and hold a primary role in semantic based video analysis, retrieval and indexing. When images and videos are obtained from natural and random sources, they need to be processed for identifying text, tracking, binarization and recognising meaningful information for succeeding actions. This proposal defines a solution with assistance of Spectral Graph Wave Transform (SGWT) technique for localizing and extracting text information from images and videos. K Means clustering technique precedes the SGWT process to group features in an image from a quantifying Hill Climbing algorithm. Precision, Sensitivity, Specificity and Accuracy are the four parameters which declares the efficiency of proposed technique. Experimentation is done from training sets from ICDAR and YVT for videos.

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