Rui Wang, Yixian Zhu, Sen Lu, Kaiming Yang, Yu Zhu
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引用次数: 0
Abstract
Wafer bonding is a critical process in 3D integration, and overlay (OVL) metrology is essential for its success. Accurately positioning the centre of OVL targets is fundamental for effective metrology. However, the identification and localization of target centres become challenging due to complex shapes and unexpected features, such as rounded corners, that can arise during manufacturing. An algorithm is proposed to tackle this challenge by employing customizable shape fitting. This method begins with the extraction of sub-pixel edge points, followed by applying a Hough transform to group and smooth these points, thereby enhancing contour quality. By parameterizing the target shape based on specific points, the algorithm integrates sub-pixel traversal techniques with an optimization objective, achieving sub-pixel accuracy in centre positioning. Simulation results indicate that the algorithm can achieve a positioning accuracy of ±0.03 pixels and demonstrates robustness against noise and blur. Finally, the proposed algorithm was used to test the OVL target pair arrays fabricated by electron beam etching, confirming an accuracy of ±0.04 pixels (±6.9 nm). These results validate the algorithm's capability to meet high precision requirements for OVL target centre positioning in wafer applications.
期刊介绍:
The IET Image Processing journal encompasses research areas related to the generation, processing and communication of visual information. The focus of the journal is the coverage of the latest research results in image and video processing, including image generation and display, enhancement and restoration, segmentation, colour and texture analysis, coding and communication, implementations and architectures as well as innovative applications.
Principal topics include:
Generation and Display - Imaging sensors and acquisition systems, illumination, sampling and scanning, quantization, colour reproduction, image rendering, display and printing systems, evaluation of image quality.
Processing and Analysis - Image enhancement, restoration, segmentation, registration, multispectral, colour and texture processing, multiresolution processing and wavelets, morphological operations, stereoscopic and 3-D processing, motion detection and estimation, video and image sequence processing.
Implementations and Architectures - Image and video processing hardware and software, design and construction, architectures and software, neural, adaptive, and fuzzy processing.
Coding and Transmission - Image and video compression and coding, compression standards, noise modelling, visual information networks, streamed video.
Retrieval and Multimedia - Storage of images and video, database design, image retrieval, video annotation and editing, mixed media incorporating visual information, multimedia systems and applications, image and video watermarking, steganography.
Applications - Innovative application of image and video processing technologies to any field, including life sciences, earth sciences, astronomy, document processing and security.
Current Special Issue Call for Papers:
Evolutionary Computation for Image Processing - https://digital-library.theiet.org/files/IET_IPR_CFP_EC.pdf
AI-Powered 3D Vision - https://digital-library.theiet.org/files/IET_IPR_CFP_AIPV.pdf
Multidisciplinary advancement of Imaging Technologies: From Medical Diagnostics and Genomics to Cognitive Machine Vision, and Artificial Intelligence - https://digital-library.theiet.org/files/IET_IPR_CFP_IST.pdf
Deep Learning for 3D Reconstruction - https://digital-library.theiet.org/files/IET_IPR_CFP_DLR.pdf