Identification of Machining Chatter Marks on Surfaces of Automotive Valve Seats

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Hagay Bamberger ◽  
Saikrishnan Ramachandran ◽  
En Hong ◽  
Reuven Katz
Keyword(s):  
Processing Technique ◽  
Image Processing Technique ◽  
Inspection System ◽  
Circle Fitting ◽  
Machining Processes ◽  
Robust Identification ◽  
Machining Chatter ◽  
Occurrence Matrix ◽  
First Time ◽  
Chatter Marks

In this paper, we propose a method for inspecting machining chatter marks on automotive valve seats using image processing technique. Chatter or self-excited tool-workpiece relative vibration is unacceptable in the machining processes of valve seats, because it causes poor surface finish and can create internal leaks in the engine. Robust identification of chatter marks on machined surfaces is one of the main challenges in the realization of an automatic in-line inspection system. We suggest several methods for calculating the chatter marks severity, using circle fitting and gray level co-occurrence matrix technique, which was for the first time implemented on circular images.

scholarly journals Remotely Sensed Seasonal Shoreward Intrusion of the East Australian Current: Implications for Coastal Ocean Dynamics

2021 ◽  
Vol 13 (5) ◽  
pp. 854
Author(s):  
Senyang Xie ◽  
Zhi Huang ◽  
Xiao Hua Wang
Keyword(s):  
Austral Summer ◽  
Processing Technique ◽  
Ocean Dynamics ◽  
Image Processing Technique ◽  
East Australian Current ◽  
Shelf Circulation ◽  
Topographic Position Index ◽  
South Wales ◽  
Position Index ◽  
First Time

For decades, the presence of a seasonal intrusion of the East Australian Current (EAC) has been disputed. In this study, with a Topographic Position Index (TPI)-based image processing technique, we use a 26-year satellite Sea Surface Temperature (SST) dataset to quantitatively map the EAC off northern New South Wales (NSW, Australia, 28–32°S and ~154°E). Our mapping products have enabled direct measurement (“distance” and “area”) of the EAC’s shoreward intrusion, and the results show that the EAC intrusion exhibits seasonal cycles, moving closer to the coast in austral summer than in winter. The maximum EAC-to-coast distance usually occurs during winter, ranging from 30 to 40 km. In contrast, the minimum distance usually occurs during summer, ranging from 15 to 25 km. Further spatial analyses indicate that the EAC undergoes a seasonal shift upstream of 29°40′S and seasonal widening downstream. This is the first time that the seasonality of the EAC intrusion has been confirmed by long-term remote-sensing observation. The findings provide new insights into seasonal upwelling and shelf circulation previously observed off the NSW coast.

Handheld Device Based on Image Processing Technique for Detecting Multiple Diseases of Apple Leaves

2019 ◽  
Vol 16 (10) ◽  
pp. 4160-4163 ◽  
Author(s):  
Swati Singh ◽  
Sheifali Gupta ◽  
Rupesh Gupta
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Disease Detection ◽  
Normal Leaf ◽  
Handheld Device ◽  
Apple Leaves ◽  
Occurrence Matrix ◽  
Conventional Detection

The present invention discloses a handheld device for multiple disease detection from apple leaf and method thereof. An algorithm is developed in combination with image processing and gray level co occurrence matrix for the classification of normal leaf and diseased apple leaf. The device performs image processing by segmentation of the image and then by using extracted features. The classification and detection of these diseases impart an early solution to the farmers leading less harm to the apple crops. Conventional Detection of the diseases through naked eye can sometimes be faulty. Therefore the device of present invention helps farmers to detect the accurate diseases and provide timely solutions for the same. The present invention increases the throughput and reduces subjectiveness of the previously used conventional methods by proving early and precise disease detection from apple leaves.

scholarly journals Effective Strain Image Sequence Selection by Using Semi-Automated Image Processing Technique

2021 ◽  
pp. 8-13
Author(s):  
Gulam Mahfuz Chowdhury ◽  
Md Mahedi Hasan ◽  
Asif Ahmed ◽  
Md Wahid Tousif Rahman ◽  
Md Taslim Reza
Keyword(s):  
Effective Strain ◽  
Real Life ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Ultra Sound ◽  
Science And Engineering ◽  
Sequence Selection ◽  
Professional Doctor ◽  
Occurrence Matrix ◽  
Automated Image Processing

One fourth of the cancer detected in women worldwide is breast cancer which leads this as a major threat for women. There are many methods of detecting cancer among which ultra-sound strain imaging is one of the promising techniques. However, in strain sequence, not all the frames show clear tumor visibility. Consequently, in this paper we tested some well-defined algorithms to find only those frames where the tumor is comparatively clearly visible. We have used Mean Pixel Difference (MPD) and Gray- Level Co-occurrence Matrix (GLCM) to find the frames with better tumor visibility. We have tested our methods in several real-life cases and the results have been examined by a professional doctor. The MPD has an accuracy of 96.2% and the GLCM. Contrast has that of 55.55%. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 7, Dec 2020 P 8-13

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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