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

Author(s):  
Gulam Mahfuz Chowdhury ◽  
Md Mahedi Hasan ◽  
Asif Ahmed ◽  
Md Wahid Tousif Rahman ◽  
Md Taslim Reza

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

Author(s):  
Hagay Bamberger ◽  
Saikrishnan Ramachandran ◽  
En Hong ◽  
Reuven Katz

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.


To design and develop an automated surveillance system to detect and intimate the presence of animals, monitoring the health parameters of the trekkers and to detect fire in the dense forest. Using sensors and wireless technology that communicate to the base station using wireless communication. In this project the image processing technique is explored for the detection of animals so that any change in pattern then the trekkers and base station are alerted. For the communication process, a wireless underground sensor network is employed which has a lot of interlinked nodes. This is because internet usage is not effective in the dense and reserved forest area. Node to node communication is performed for efficient information sharing with the base station and the communication process for trekkers is carried on with wireless sensor networks thus provides warning information to the trekkers. Animal detection based applications have a very important role in many real-life situations and also detection of forest fire in dense forest is hard and fast-spreading. Therefore there must be automation and faster means of communication


2019 ◽  
Vol 16 (10) ◽  
pp. 4160-4163 ◽  
Author(s):  
Swati Singh ◽  
Sheifali Gupta ◽  
Rupesh Gupta

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.


Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya

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.


Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi

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.


Author(s):  
Yashpal Jitarwal ◽  
Tabrej Ahamad Khan ◽  
Pawan Mangal

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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