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Laser-induced Forward Transfer for Flip-chip Packaging of Single Dies

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Published on: March 20, 2015

A Novel Feature Extraction Algorithm and System for Flexible Integrated Circuit Packaging Substrate.

Dan Huang¹, Juan Wang², Yong Zeng²

¹The School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China.

|March 26, 2022

Summary

This summary is machine-generated.

This study introduces a new algorithm for detecting line defects in flexible integrated circuit substrates (FICS) without a reference template. The method accurately extracts line features, improving defect location and enabling precise measurements.

Keywords:

defect detection flexible integrated circuit packaging substrate level set function

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Area of Science:

Electrical Engineering
Computer Vision
Materials Science

Background:

Flexible integrated circuit substrates (FICS) require precise line defect detection.
Existing methods struggle with line discontinuity and inaccurate defect localization without reference templates.

Purpose of the Study:

To develop a robust line feature detection algorithm for FICS.
To overcome limitations of existing methods in identifying line defects.

Main Methods:

Acquired FICS images using a custom intelligent defect detection system.
Preprocessed images via K-means classification, median filtering, morphological filling, and closed operations to obtain binary images.
Applied a novel convexity-preserving indirect regular level set model for line feature extraction.

Main Results:

The proposed model accurately extracts line features from FICS images.
Achieved smooth line boundaries, outperforming comparative models (CV, LBF, LCV, LGIF, Order-LBF, RSF).
Demonstrated high accuracy in line feature extraction.

Conclusions:

The developed algorithm provides a foundation for high-precision line width/distance measurement and defect localization in FICS.
Offers a significant advancement in automated inspection for flexible electronics.