scholarly journals The Grading Multiple Choice Tests System via Mobile Phone using Image Processing Technique

2018 ◽  
Vol 13 (10) ◽  
pp. 260 ◽  
Author(s):  
Worawut Yimyam ◽  
Mahasak Ketcham
Keyword(s):  
Image Processing ◽  
Mobile Phone ◽  
Digital Camera ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Objective Test ◽  
Grading System ◽  
Pixel Intensity ◽  
Multiple Choice Tests ◽  
Choice Tests

Grading devices are expensive causing budget waste, in addition some are difficult to use. Therefore, an objective test grading system via Android mobile phone was developed to save cost and time in grading. The system uses image processing technique developed by Java. A camera on a mobile phone was used to capture the edge of answers and an equation of geometric simulation of digital camera sensor was applied to identify answers selected from calculation of pixel intensity in real time. The objective test grading system via Android mobile phone can work effectively and accurately more than 95%.

scholarly journals Analysis of Fine Crack Images Using Image Processing Technique and High-Resolution Camera

2021 ◽  
Vol 11 (20) ◽  
pp. 9714
Author(s):  
Hoseong Jeong ◽  
Baekeun Jeong ◽  
Myounghee Han ◽  
Dooyong Cho
Keyword(s):  
Image Processing ◽  
Crack Width ◽  
Focal Length ◽  
Great Influence ◽  
Health And Safety ◽  
Digital Camera ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Width Measurement ◽  
Working Distance

Visual inspections are performed to investigate cracks in concrete infrastructure. These activities require manpower or equipment such as articulated ladders. Additionally, there are health and safety issues because some structures have low accessibility. To deal with these problems, crack measurement with digital images and digital image processing (DIP) techniques have been adopted in various studies. The objective of this experimental study is to evaluate the optical limit of digital camera lenses as working distance increases. Three different lenses and two digital cameras were used to capture images of lines ranging from 0.1 to 0.5 mm in thickness. As a result of the experiments, it was found that many elements affect width measurement. However, crack width measurement is dependent on the measured pixel values. To accurately measure width, the measured pixel values must be in decimal units, but that is theoretically impossible. According to the results, in the case of 0.3 mm wide or wider cracks, a working distance of 1 m was secured when the focal length was 50 mm, and working distances of 3 m and 4 m were secured when the focal length was 100 mm and 135 mm, respectively. However, for cracks not wider than 0.1 mm, focal lengths of 100 mm and 135 mm showed measurability within 1 m, but a focal length of 50 mm was judged to hardly enable measurement except for certain working positions. Field measurement tests were conducted to verify measurement parameters identified by the results of the indoor experiment. The widths of actual cracks were measured through visual inspection and used for the analysis. From the evaluation, it was confirmed that the number of pixels corresponding to the working distance had a great influence on crack width measurement accuracy when using image processing. Therefore, the optimal distance and measurement guidelines required for the measurement of the size of certain objects was presented for the imaging equipment and optical equipment applied in this study.

scholarly journals Image processing-based mTICI grading after endovascular treatment for acute ischemic stroke

2021 ◽  
Vol 7 (2) ◽  
pp. 235-238
Author(s):  
Muhannad Sabieleish ◽  
Maximilian Thormann ◽  
Jonathan Metzler ◽  
Axel Boese ◽  
Michael Friebe ◽  
...  
Keyword(s):  
Image Processing ◽  
Ischemic Stroke ◽  
Endovascular Treatment ◽  
Mechanical Thrombectomy ◽  
Processing Technique ◽  
Automated System ◽  
Image Processing Technique ◽  
Pixel Intensity ◽  
Mca Occlusion ◽  
Starting Point

Abstract Introduction : The grade of reperfusion after endovascular treatment of ischemic stroke e.g. mechanical thrombectomy is determined based on the mTICI score. The mTICI score shows significant interrater variability; it is usually biased towards better reperfusion results if selfassessed by the operator. We therefore developed a semiautomated image processing technique for assessing and evaluating the degree of reperfusion independently, resulting in a more objective mTICI score. Methods: Fifty angiography datasets of patients who were treated with mechanical thrombectomy for middle cerebral artery (MCA) occlusion were selected from our database. Image datasets were standardized by adjustment of field of view and orientation. Based on pixel intensity features, the internal carotid artery (ICA) curve was detected automatically and used as a starting point for identifying the target downstream territory (TDT) of the MCA on the DSA series. Furthermore, a grid with predefined dimensions was used to divide the TDT into checkzones and be classified as perfused or unperfused. Results: The algorithm detected the TDT and classified each zone of the grid as perfused or unperfused. Lastly, the percentage of the perfused area in the TDT was calculated for each patient and compared to the grading of experienced clinical users. Conclusion: A semi-automatic image-processing workflow was developed to evaluate perfusion rate based on angiographic images. The approach can be used for the objective calculation of the mTICI score. The semi-automatic grading is currently feasible for MCA occlusion but can be extended for other brain territories. The work shows a starting point for a machine learning approach to achieve a fully automated system that can evaluate and give an accurate mTICI score to become a common AI-based grading standard in the coming near future.

scholarly journals Detection of Counterfeit Indian Currency Note using Image Processing

2019 ◽  
Vol 9 (1) ◽  
pp. 2440-2447
Keyword(s):  
Image Processing ◽  
Good Accuracy ◽  
Digital Camera ◽  
Processing Technique ◽  
Advanced Technology ◽  
Image Processing Technique ◽  
Accuracy Rate ◽  
Common People ◽  
Legal Sanction ◽  
Currency Note

Most of the country suffering from the problem of counterfeit note. Indian is also part of such problem. As advance in technology, it is possible for anyone to print counterfeit note. Such counterfeit notes are produced without the legal sanction of Government and production of such notes degrades the economy of any country. After demonetization in India Newly 500 and 2000 currency notes are launched but due to misuse of advanced technology, fake currency of such notes are produced by counterfeiter due to its high value and circulated in most of the part of our country. With the production and circulation of such counterfeit notes, it becomes difficult for common people to differentiate whether the currency is real or fake as they differentiate on the basis of physical appearance which effects the economy of our country. Here a system is proposed to differentiate between real and fake note which is based on the image processing technique and implemented in MATLAB. In this technique, first the image of 500 and 2000 rupee note is captured through the digital camera and perform preprocessing in order to remove noise and then mean intensity of RGB channels of image is calculated and further the three different features including Latent image, RBI Logo and denomination numeral with Rupee symbol are extracted to differentiate between real and fake note. The performance of the proposed system achieves good accuracy rate.

A Novel Approach of Controlling Stoppage of Drip Infusion Using Image Processing on Raspberry PI Platform

2021 ◽  
Vol 58 (S) ◽  
pp. 65-72
Author(s):  
Hartono Pranjoto ◽  
Lanny Agustine ◽  
Diana Lestariningsih ◽  
Yesiana Dwi Wahyu Werdani ◽  
Widya Andyardja ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Detection Algorithm ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Novel Approach ◽  
Pinch Valve ◽  
Canny Edge ◽  
Infusion Fluid

Intravenous drip diffusion is a common practice to treat patients in hospitals. During treatment, nurses must check the condition of the infusion bag frequently before running out of fluid. This research proposes a novel method of checking the infusion bag using an image processing technique on a compact Raspberry PI platform. The infusion monitoring system proposed here is based solely on capturing the image of the infusion bag and the accompanying bag/ tube. When the infusion fluid enters the patient, the surface of the liquid will decrease, and at the end will reach the bottom of the infusion bag. When the image of the fluid surface touches the bottom of the infusion bag, a mechanism will trigger a relay, and then activate a pinch valve to stop the flow of the infusion fluid before it runs out. The entire system incorporates a digital camera and Raspberry as the image processor. The surface of the liquid is determined using the Canny Edge Detection algorithm, and its relative position in the tube is determined using the Hough Line Transform. The raw picture of the infusion bag and the processed image are then sent via a wireless network to become part of a larger system and can be monitored via a simple smartphone equipped with the proper application, thus becoming an Internet of Things (IoT). With this approach, nurses can carry on other tasks in caring for the patients while this system substitutes some work on checking the infusion fluid.

scholarly journals The study of water-head measurement shown in a single tube manometer by use of easy image-processing technique

2019 ◽  
Vol 213 ◽  
pp. 02102
Author(s):  
Yoshifumi Yokoi
Keyword(s):  
Image Processing ◽  
Water Level ◽  
Digital Camera ◽  
Image Data ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Low Flow ◽  
Single Tube ◽  
Water Head ◽  
Processing Measurement

This study proposes the technique which can perform pressure measurement by the low flow velocity which is performed by flow visualization. The technique is the following. The water level image accompanied by the scale shown in a single tube manometer is photographed with a digital camera or a digital camcorder. And image-processing measurement of the image data is carried out in the length of the water level by computer. As verification of the technique, the measurement comparison result of the pressure distribution on the surface of a circular cylinder set in the stream was compared with the previous result. The result was good. It proved that the technique is measurable also by a minute water-head. Furthermore, examination was performed about the validity, the reliability, and the operativity of the technique. As a result, even if who did operation of image-processing measurement, it was shown that high resolution and good accuracy are obtained.

A New Image Processing Technique for STEM

1974 ◽  
Vol 32 ◽  
pp. 432-433
Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Elastic Scattering ◽  
Field Emission ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Energy Analyzer ◽  
Scanning Microscope ◽  
Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

An Enhanced Technique for Classification of Fruits using Shape Color and Texture Features

2017 ◽  
Vol 7 (7) ◽  
pp. 408
Author(s):  
Yashpal Jitarwal ◽  
Tabrej Ahamad Khan ◽  
Pawan Mangal
Keyword(s):  
Image Processing ◽  
Texture Features ◽  
Automatic Classification ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Advance Technique ◽  
Time Required ◽  
Fruit Sorting ◽  
Human Inspection

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.

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