Sarvesh Pandey
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Sarvesh Pandey has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Anuja Shrestha
Department of Mechanical Engineering, School of Engineering, Kathmandu University, Dhulikhel, Kavrepalanchok P.O. Box 6250, Nepal
1 shared publication - Anwit Pokharel
Department of Mechanical Engineering, School of Engineering, Kathmandu University, Dhulikhel, Kavrepalanchok P.O. Box 6250, Nepal
1 shared publication - Cheol Sang Kim
Department of Bionanotechnology and Bioconvergence Engineering, Graduate School, Jeonbuk National University, Jeonju, Republic of Korea
1 shared publication - Eliza Sapkota
Laboratory of Lean Satellite Enterprises and In-Orbit Experiments (LaSEINE) Kyushu Institute of Technology, 1-1 Sensui Tobata-ku, Kitakyushu 804-8550, Fukuoka, Japan
1 shared publication - Ho Jong Kim
Division of Mechanical Design Engineering, Chonbuk National University, Jeonju 561-756, Republic of Korea
1 shared publication - Ranjit Shrestha
Department of Mechanical Engineering, School of Engineering, Kathmandu University, Dhulikhel P.O. Box 6250, Nepal
1 shared publication
Latest Publications
- Open Access
A Study on the Effectiveness of Spatial Filters on Thermal Image Pre-Processing and Correlation Technique for Quantifying Defect Size
Thermal imaging plays a vital role in structural health monitoring of various materials and provides insight into the defect present due to aging, deterioration, and fault during construction. This study investigated the effectiveness of spatial filters during pre-processing of thermal images and a correlation technique in post-processing, as well as exploited its application in non-destructive testing and evaluation of defects in steel structures. Two linear filters (i.e., Gaussian and Window Averaging) and a non-linear filter (i.e., Median) were implemented during pre-processing of a pulsed thermography image sequence. The effectiveness of implemented filters was then assessed using signal to noise ratio as a quality metric. The result of pre-processing revealed that each implemented filter is capable of reducing impulse noise and producing high-quality images; additionally, when comparing the signal to noise ratio, the Gaussian filter dominated both Window Averaging and Median filters. Defect size was determined using a correlation technique on a sequence of pulsed thermography images that had been pre-processed with a Gaussian filter. Finally, it is concluded that the correlation technique could be applied to the fast measurement of defect size, even though the accuracy may depend on the detection limit of thermography and defect size to depth ratio.
Open AccessA Study on the Effectiveness of Spatial Filters on Thermal Image Pre-Processing and Correlation Technique for Quantifying Defect Size
Thermal imaging plays a vital role in structural health monitoring of various materials and provides insight into the defect present due to aging, deterioration, and fault during construction. This study investigated the effectiveness of spatial filters during pre-processing of thermal images and a correlation technique in post-processing, as well as exploited its application in non-destructive testing and evaluation of defects in steel structures. Two linear filters (i.e., Gaussian and Window Averaging) and a non-linear filter (i.e., Median) were implemented during pre-processing of a pulsed thermography image sequence. The effectiveness of implemented filters was then assessed using signal to noise ratio as a quality metric. The result of pre-processing revealed that each implemented filter is capable of reducing impulse noise and producing high-quality images; additionally, when comparing the signal to noise ratio, the Gaussian filter dominated both Window Averaging and Median filters. Defect size was determined using a correlation technique on a sequence of pulsed thermography images that had been pre-processed with a Gaussian filter. Finally, it is concluded that the correlation technique could be applied to the fast measurement of defect size, even though the accuracy may depend on the detection limit of thermography and defect size to depth ratio.