Adaptive directional cubic convolution for integrated circuit chip defect image interpolation

被引:0
|
作者
Chao Y. [1 ]
Ma C. [1 ]
Shan W. [1 ]
Feng J. [1 ]
Zhang Z. [2 ]
机构
[1] School of Mechanical Engineering, Jiangsu University of Technology, Changzhou, Jiangsu
[2] School of Mechanical Engineering, Southeast University, Nanjing, Jiangsu
基金
中国国家自然科学基金;
关键词
Bicubic; Image interpolation; Integrated circuit chip; Otsu thresholding;
D O I
10.46300/9106.2021.15.117
中图分类号
学科分类号
摘要
—An adaptive directional cubic convolution interpolation method for integrated circuit (IC) chip defect images is proposed in this paper, to meet the challenge of preserving edge and texture information. In the proposed method, Otsu thresholding technique is employed to distinguish strong edge pixels from weak ones and texture regions, and estimate the direction of strong edges, adaptively. Boundary pixels are pre-interpolated using the original bicubic interpolation method to help improve the interpolation accuracy of the interior pixels. The experimental results of both classic test images and IC chip defect images demonstrate that the proposed method outperforms the competing methods with better edge and texture preservation, interpolation quality, more natural visual effect of the interpolated images and reasonable computational time. The proposed method can provide high quality IC chip images for defect detection and has been successfully applied on practical vision inspection for IC chips. © 2021, North Atlantic University Union NAUN. All rights reserved.
引用
收藏
页码:1084 / 1090
页数:6
相关论文
共 32 条
  • [1] Image zooming using directional cubic convolution interpolation
    Zhou, D.
    Shen, X.
    Dong, W.
    [J]. IET IMAGE PROCESSING, 2012, 6 (06) : 627 - 634
  • [2] Adaptive cubic convolution based image interpolation approach
    Li, Chunlong
    Pan, Haixia
    Wang, Huafeng
    [J]. Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2014, 40 (10): : 1463 - 1468
  • [3] A research on medical image interpolation based on cubic convolution and adaptive interpolation
    Wang, Anna
    Luo, Kai
    Li, Peng
    Zhang, Xinhua
    [J]. IMECS 2007: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, VOLS I AND II, 2007, : 536 - +
  • [4] CUBIC CONVOLUTION INTERPOLATION FOR DIGITAL IMAGE-PROCESSING
    KEYS, RG
    [J]. IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1981, 29 (06): : 1153 - 1160
  • [5] Performance Evaluation of Halide Auto -Scheduler with Directional Cubic Convolution Interpolation
    Nogami, Haruki
    Oishi, Sou
    Sasaki, Tomohiro
    Maeda, Yoshihiro
    Fukushima, Norishige
    [J]. INTERNATIONAL WORKSHOP ON ADVANCED IMAGING TECHNOLOGY, IWAIT 2023, 2023, 12592
  • [6] FPGA Accelerated Bi-Cubic Convolution for Image Interpolation
    Choudhary, Ankit
    Kodavati, S. K. Vaibhav
    Mythili, B.
    Anjaneyulu, R. V. G.
    Sarma, M. Manju
    [J]. 2023 IEEE 30TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING, DATA, AND ANALYTICS, HIPC 2023, 2023, : 189 - 193
  • [7] Image interpolation by two-dimensional parametric cubic convolution
    Shi, Jiazheng
    Reichenbach, Stephen E.
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2006, 15 (07) : 1857 - 1870
  • [8] Image data compression using cubic convolution spline interpolation
    Truong, TK
    Wang, LJ
    Reed, IS
    Hsieh, WS
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2000, 9 (11) : 1988 - 1995
  • [9] PACKAGE CHIP DEFECT REDUCTION ON INTEGRATED CIRCUIT
    Kulpiya, Seri
    Senjuntichai, Angsumalin
    [J]. PROGRESS IN MECHATRONICS AND INFORMATION TECHNOLOGY, PTS 1 AND 2, 2014, 462-463 : 578 - 584
  • [10] Medical image data compression using cubic convolution spline interpolation
    Truong, TK
    Wang, LJ
    [J]. CENTRAL AUDITORY PROCESSING AND NEURAL MODELING, 1998, : 175 - 188