An alternative robust and High Reliability optical flow based on Horn-Schunck Algorithm using median filter and confidence based technique

2012 ◽  
Author(s):  
Darun Kesrarat ◽  
Vorapoj Patanavijit
Keyword(s):  
Optical Flow ◽  
High Reliability ◽  
Median Filter

scholarly journals Grey-Level Cooccurrence Matrix Performance Evaluation for Heading Angle Estimation of Moveable Vision System in Static Environment

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Zairulazha Zainal ◽  
Rizauddin Ramli ◽  
Mohd Marzuki Mustafa
Keyword(s):  
Optical Flow ◽  
Vision System ◽  
Median Filter ◽  
Estimation Method ◽  
Mean Absolute Deviation ◽  
Grey Level ◽  
Absolute Deviation ◽  
Area Of Interest ◽  
Flow Generation ◽  
Heading Angle

A method of extracting information in estimating heading angle of vision system is presented. Integration of grey-level cooccurrence matrix (GLCM) in an area of interest selection is carried out to choose a suitable region that is feasible for optical flow generation. The selected area is employed for optical flow generation by using Horn-Schunck method. From the generated optical flow, heading angle is estimated and enhanced via moving median filter (MMF). In order to ascertain the effectiveness of GLCM, we compared the result with a different estimation method of optical flow which is generated directly from untouched greyscale images. The performance of GLCM is compared to the true heading, and the error is evaluated through mean absolute deviation (MAE). The result ensured that GLCM can improve the estimation result of the heading angle of vision system significantly.

scholarly journals Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Young Jae Kim ◽  
Kwang Gi Kim
Keyword(s):  
Macular Degeneration ◽  
High Reliability ◽  
Median Filter ◽  
Age Related Macular Degeneration ◽  
Optic Disk ◽  
Fundus Image ◽  
Difference Image ◽  
Age Related ◽  
Renyi’S Entropy ◽  
The Difference

Existing drusen measurement is difficult to use in clinic because it requires a lot of time and effort for visual inspection. In order to resolve this problem, we propose an automatic drusen detection method to help clinical diagnosis of age-related macular degeneration. First, we changed the fundus image to a green channel and extracted the ROI of the macular area based on the optic disk. Next, we detected the candidate group using the difference image of the median filter within the ROI. We also segmented vessels and removed them from the image. Finally, we detected the drusen through Renyi’s entropy threshold algorithm. We performed comparisons and statistical analysis between the manual detection results and automatic detection results for 30 cases in order to verify validity. As a result, the average sensitivity was 93.37% (80.95%~100%) and the average DSC was 0.73 (0.3~0.98). In addition, the value of the ICC was 0.984 (CI: 0.967~0.993, p<0.01), showing the high reliability of the proposed automatic method. We expect that the automatic drusen detection helps clinicians to improve the diagnostic performance in the detection of drusen on fundus image.

Failure Analysis With the Scanning Electron Microscope

1972 ◽  
Vol 30 ◽  
pp. 482-483
Author(s):  
John R. Devaney
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Integrated Circuits ◽  
Failure Analysis ◽  
High Reliability ◽  
Military Applications ◽  
Small Structure ◽  
Useful Life ◽  
Insight Into ◽  
Scanning Electron

Occasionally in history, an event may occur which has a profound influence on a technology. Such an event occurred when the scanning electron microscope became commercially available to industry in the mid 60's. Semiconductors were being increasingly used in high-reliability space and military applications both because of their small volume but, also, because of their inherent reliability. However, they did fail, both early in life and sometimes in middle or old age. Why they failed and how to prevent failure or prolong “useful life” was a worry which resulted in a blossoming of sophisticated failure analysis laboratories across the country. By 1966, the ability to build small structure integrated circuits was forging well ahead of techniques available to dissect and analyze these same failures. The arrival of the scanning electron microscope gave these analysts a new insight into failure mechanisms.

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