A Study on a Focus Value Quantification Algorithm Applicable to the Vision System

Background/Objectives: Recent development of the IT industry has led to active convergence among industries, and the field of semiconductors has especially shown decreasing size and weight of products. As smaller products are resulting in management of production processes using the vision system, this paper proposes a focus value quantification algorithm to acquire images for the detection of defects in semiconductor packages. Methods/Statistical analysis: An active focus measurement method that uses an image processing technique to improve autofocusing efficiency of camera lenses by enhancing the detection of defects in semiconductor packages was applied. After acquiring images of target packages, the SMD(Sum Modules Difference), Tenengrad, SML(Sum Modified Laplacian) and LOG(Laplacian of Gaussian) algorithms were used on the acquired images to calculate focus values. Quantification was performed on a large quantity of focus values. Findings: Camera is a very important device in the vision system, and adjusting focus of camera lenses is essential in acquiring accurate images to detect defects in semiconductor packages. In general, time required for focus adjustment is determined as the sum of time taken to calculate the focus value for moving a camera to the image acquisition position and time taken to calculate the focus value from the acquired image. It would be necessary for users and hosts at industrial sites to perform interpretation of the focus value quickly and accurately. However, since various existing algorithms have extremely large focus values and are difficult to interpret, this paper proposes an algorithm that can interpret focus values quickly through quantification. Based on the comparison of information before and after quantification, the position of maximum focus value was measured to be the same. The proposed algorithm can increase efficiency of semiconductor package testing by shortening time required to interpret the focus value in the device configuration stage. Improvements/Applications: Future studies should be conducted on an algorithm to improve speed of focus value calculation and an algorithm to acquire image according to wavelength of lighting and conditions of lenses.

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Publication Details

Journal
International Journal of Engineering & Technology
Published
2026-04-25
DOI
https://doi.org/10.14419/ijet.v7i3.24.22673
Primary Topic
Image Processing Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

A Study on a Focus Value Quantification Algorithm Applicable to the Vision System

Koo-Rack Park, Seong-Ik Kim, Dong-Hyun Kim
International Journal of Engineering & Technology
Image Processing Techniques and Applications
article

A Study on a Focus Value Quantification Algorithm Applicable to the Vision System

Koo-Rack Park, Seong-Ik Kim, Dong-Hyun Kim
article en

Abstract

Background/Objectives: Recent development of the IT industry has led to active convergence among industries, and the field of semiconductors has especially shown decreasing size and weight of products. As smaller products are resulting in management of production processes using the vision system, this paper proposes a focus value quantification algorithm to acquire images for the detection of defects in semiconductor packages. Methods/Statistical analysis: An active focus measurement method that uses an image processing technique to improve autofocusing efficiency of camera lenses by enhancing the detection of defects in semiconductor packages was applied. After acquiring images of target packages, the SMD(Sum Modules Difference), Tenengrad, SML(Sum Modified Laplacian) and LOG(Laplacian of Gaussian) algorithms were used on the acquired images to calculate focus values. Quantification was performed on a large quantity of focus values. Findings: Camera is a very important device in the vision system, and adjusting focus of camera lenses is essential in acquiring accurate images to detect defects in semiconductor packages. In general, time required for focus adjustment is determined as the sum of time taken to calculate the focus value for moving a camera to the image acquisition position and time taken to calculate the focus value from the acquired image. It would be necessary for users and hosts at industrial sites to perform interpretation of the focus value quickly and accurately. However, since various existing algorithms have extremely large focus values and are difficult to interpret, this paper proposes an algorithm that can interpret focus values quickly through quantification. Based on the comparison of information before and after quantification, the position of maximum focus value was measured to be the same. The proposed algorithm can increase efficiency of semiconductor package testing by shortening time required to interpret the focus value in the device configuration stage. Improvements/Applications: Future studies should be conducted on an algorithm to improve speed of focus value calculation and an algorithm to acquire image according to wavelength of lighting and conditions of lenses.

International Journal of Engineering & TechnologyVol. 7(3.24)
Industry, innovation and infrastructure
Openalex Percentile: Top 12%
Image Processing Techniques and Applications
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