EVALUATION OF THE EDGE PROFILE SHIFTING BASED ON STATISTICAL APPROACH TO IMPROVE THE EDGE-BASED MTF MEASUREMENT

This study aims to evaluate the accuracy of edge profile shifting based on a statistical approach to improve the edge-based modulation transfer function (MTF) measurement using the slanted-edge phantom. A slanted-edge phantom was computationally developed with two materials, a water and a material of 120 HU. The spatial resolution of the phantom was varied from 0.3 to 1.25 cycle/mm and the slanted angle was varied from 0° to 10°. The statistical shifting was performed by shifting the treated ESF backward and forward by up to 10 pixels (increment of 1 pixel). At each shift, the similarity between the shifted and reference ESFs was calculated using mean squared error (MSE). The statistical edge-MTF was compared against the traditional edge-MTF and the point-MTF as the gold standard. The statistical edge-MTF approach had similar results against the point-MTF compared to the traditional edge-MTF. At a slanted angle less than 8°, the statistical edge-MTF was comparable to the point-MTF with a difference about 2%. For slanted angles more than 8°, the difference was around 5%. By contrast, the non-statistical edge-MTF approach produced larger differences as the slanted angle increased. The statistical approach for measuring edge-MTF is more robust compared to the traditional edge-MTF approach.

Authors

Institutions

Publication Details

Journal
Jurnal Teknologi
Published
2025-03-12
DOI
https://doi.org/10.11113/jurnalteknologi.v87.22385
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
1.24
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EVALUATION OF THE EDGE PROFILE SHIFTING BASED ON STATISTICAL APPROACH TO IMPROVE THE EDGE-BASED MTF MEASUREMENT

Ariij Naufal, Choirul Anam, Geoff Dougherty, Riska Amilia et al.
1 citations
Jurnal Teknologi
Industrial Vision Systems and Defect Detection
1.24
article

EVALUATION OF THE EDGE PROFILE SHIFTING BASED ON STATISTICAL APPROACH TO IMPROVE THE EDGE-BASED MTF MEASUREMENT

Ariij Naufal, Choirul Anam, Geoff Dougherty, Riska Amilia, Karrar Mahdi Badi
article en
1 citations

Abstract

This study aims to evaluate the accuracy of edge profile shifting based on a statistical approach to improve the edge-based modulation transfer function (MTF) measurement using the slanted-edge phantom. A slanted-edge phantom was computationally developed with two materials, a water and a material of 120 HU. The spatial resolution of the phantom was varied from 0.3 to 1.25 cycle/mm and the slanted angle was varied from 0° to 10°. The statistical shifting was performed by shifting the treated ESF backward and forward by up to 10 pixels (increment of 1 pixel). At each shift, the similarity between the shifted and reference ESFs was calculated using mean squared error (MSE). The statistical edge-MTF was compared against the traditional edge-MTF and the point-MTF as the gold standard. The statistical edge-MTF approach had similar results against the point-MTF compared to the traditional edge-MTF. At a slanted angle less than 8°, the statistical edge-MTF was comparable to the point-MTF with a difference about 2%. For slanted angles more than 8°, the difference was around 5%. By contrast, the non-statistical edge-MTF approach produced larger differences as the slanted angle increased. The statistical approach for measuring edge-MTF is more robust compared to the traditional edge-MTF approach.

Jurnal TeknologiVol. 87(3)
Diponegoro University (ID), California State University, Channel Islands (US), University of Al-Qadisiyah (IQ)
Openalex Percentile: Top 22%
Industrial Vision Systems and Defect Detection
1.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.