scholarly journals Feedback Method Based on Image Processing for Detecting Human Body via Flying Robot

2013 ◽  
Vol 4 (6) ◽  
pp. 35-44 ◽  
Author(s):  
Bahram Lavi Sefidgari
Keyword(s):  
Image Processing ◽  
Human Body ◽  
Feedback Method ◽  
Flying Robot

Segmentation of Different Tissues of Brain From MR Image

2019 ◽  
pp. 142-180
Author(s):  
Ankur Priyadarshi
Keyword(s):  
Image Processing ◽  
Human Body ◽  
Medical Image Processing ◽  
The Body ◽  
Tissue Type ◽  
Mr Image ◽  
Research Fields ◽  
Multiple Thresholds ◽  
Initial Segmentation ◽  
Different Tissues

In the most recent couple of decades, medical image processing stood out within picture preparing research fields because of its nonintrusive nature. Restorative imaging modalities, for example, MRI, CT filter, for the most part, rely upon computer imaging innovation to create or show advanced pictures of the inward organs of the human body, which causes the medicine professionals to envision the internal bits of the body. Here the proposed algorithm is thresholding different tissue type of brain MR image. Modes of the histogram represent different tissue types in brain MR image. So, this algorithm depends on the principle of finding maxima and minima using differentiation of the smoothed histogram. Using discrete differentiation, the author finds the multiple thresholds of brain MR image by selecting proper location of minima. The algorithm can be used as an initial segmentation of different tissue types of brain MR image for further accurate detection of the regions.

The Fundamentals of Biomedical Image Processing

2019 ◽  
pp. 185-208
Author(s):  
Kirti Raj Bhatele ◽  
Vivek Gupta ◽  
Kamlesh Gupta ◽  
Prashant Shrivastava
Keyword(s):  
Image Processing ◽  
Medical Imaging ◽  
Human Body ◽  
Digital Images ◽  
Modern Society ◽  
Medical Procedures ◽  
Biomedical Image Processing ◽  
Anatomy And Physiology ◽  
Biomedical Image ◽  
The Impact

This chapter provides a brief introduction to the various fundamentals and concepts related to the basics of the biomedical image processing. Medical imaging processing comprises various techniques and processes that are used to create images of human body for clinical purposes and medical procedures for the purpose of diagnosis or examination of disease. Digital image processing along with its suitable components and computer-simulated algorithms are implemented using computers to perform the image analysis of digital images. The study of normal anatomy and physiology of human body is made as a part of diagnosis process. Though medical imaging of various organs and tissues can be performed for medical examination purposes, the impact of digital images on modern society is tremendous and image processing has become a critical component of science and technology related to the biomedical image processing.

Vibration Measurement and Analysis Using Image Processing Method

Volume 2 ◽  
2004 ◽  
Author(s):  
Roya Narimani ◽  
Maryam Hoviattalab ◽  
Arash Abadpour ◽  
Azadeh Yadolahi
Keyword(s):  
Image Processing ◽  
Human Body ◽  
Mechanical Impedance ◽  
Displacement Function ◽  
The Body ◽  
Shaking Table ◽  
Vibration Measurement ◽  
Whole Body ◽  
Sinusoidal Vibration ◽  
Body Vibration

A large number of people are exposed to whole body vibration in their occupational life. Measuring vibration is an important tool in rehabilitation and biomechanical fields of research. We have proposed image processing as a new method to record and determine the frequency response of human body. The arranged set up for forced vibration consisted of an AC motor, a variable speed drive unit and a shaking table for producing one directional sinusoidal vibration. Volunteers were asked to stand on the shaking table at a relaxed posture. Two digital camcorders were used to capture the motion of colored pencil-dot markers on the skin of human body (forehead) and on the edge of the shaking table. After color spotting each frame, the binary image results were processed using new circle factor criteria proposed in this work, for fast finding circles based on second order statistics. The extracted points were calibrated using our own extended version of the direct linear transformation (DLT) method. Subsequently Vibration measuring software has been completely developed in Borland Delphi 5.0. Finally obtained displacement function of the body and the shaking table has been used in conjunction with Matlab 6.5 to prepare a proper algorithm for analyzing human body vibration. We discussed mechanical characteristics of the body by obtaining mechanical impedance and transmissibility from the shaking table to the head as example applications of the conducted software. The important point is the fact that all devices used in our developed measurement system are usually available in a biomechanics laboratory where a Gait system is functioning. This gives the opportunity for such laboratory to add vibration measurement to its capabilities without much excessive costs. The system has the advantage of lower noise sensitivity in comparison to accelerometer. The main advantage of this method is working with a simple user-familiar hardware with no external device attached to the subject and also a user-friendly-software.

scholarly journals ABSTRACT Various body parts or organs can be analysed to identify the different diseases in the human body. Fingernail analysis is one of the ways to identify disease in the human body. Nails are the body part which are farthest from the heart and therefore receive oxygen at last. As a result the nails are the first who show the symptoms of a disease in the human body. Fingernails can be easily captured for diagnosis and there are no heavy equipment or no specific conditions required to use nail image for disease diagnosis, like in other tests and scanning processes. Human nails deliver beneficial information about complaints or any nutritive imbalances in the human body depending upon their shape, texture and colour. In human beings, numerous systemic and skin diseases can be easily analyzed through careful examination of nails of both the limbs. A lot of nail illnesses have been found to be primary signs of numerous underlying systemic illnesses. The colour, texture or shape changes in nails are signs of many diseases mainly affecting nails. Considering all these properties of nails a system is proposed that uses digital image processing (DIP) methods for identifying such changes in the human nail to get more precise results and predict numerous diseases effortlessly. With the emerging Internet of Things (IOT) concept the generated report is made available remotely, this will help users to reduce transportation efforts. As the system has to deal with large and private data, the security of data must be ensured. To keep the data confidential, the Blockchain concept which is one of the most emerging concepts in the field of data management is used. The paper contains the implementation of the digital image processing for feature extraction of nail images, usage of IOT (ThingSpeak cloud) for data storage and implementation of Blockchain to keep the system secured and theft free. KEY WORDS: Int ernet of thin gs (IOT), Image proc essin g, Thin gSpeak, RG B vavalues, Mean pi xel vavalues, Bloc kchain , Hash key. Disease Diagnostic System: Abnormalities in Human Nail

2020 ◽  
Vol 13 (14) ◽  
pp. 452-457
Author(s):  
Pranav S. Wazarkar
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Human Body ◽  
Digital Image ◽  
Skin Diseases ◽  
Disease Diagnosis ◽  
The Body ◽  
Careful Examination ◽  
Human Beings ◽  
Human Nail

Human motion analysis and action scoring technology for sports training based on computer vision features

2021 ◽  
pp. 1-9
Author(s):  
Yong Bai ◽  
Yinggang Chen
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Digital Image Processing ◽  
Human Body ◽  
Median Filter ◽  
Human Movement ◽  
Human Motion ◽  
Human Motion Analysis ◽  
Recognition Model ◽  
Frame Difference

With the advent of the information age, computer-related application research has become more and more extensive, human motion analysis and action scoring based on computer vision have gradually become the focus of attention. In order to adapt to the development of the times and solve the problems related to the analysis of human motion, the experiment analyzed the similarity of eight common human movement behaviors, analyze the movement speed of men and women under sports training, and analyzed the accuracy of the human body motion recognition model in the two cases of the original gray data and the frame difference channel, finally, the denoising performance of four different algorithms of SMF, EMF, RAMF and median filter algorithm in digital image processing is analyzed. The final result shows that there is a big similarity between the same kind of human movement behavior, the accuracy rate of the frame difference channel human body recognition model is higher than that of the original gray data recognition model, and digital image processing median filter algorithm has good image denoising performance.

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