HDR Microscopy Image Fusion for Semiconductor Defect Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing semiconductor workpiece imaging systems face inaccuracies due to limited dynamic range and alignment issues when stitching multiple images, leading to challenges in detecting and characterizing micron-scale defects and features during manufacturing.
Innovation Solution
A semiconductor workpiece imaging system that obtains multiple images at varying radiation intensities and generates a composite high dynamic range (HDR) image, spatially correlating these images to improve accuracy and detail in defect detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are obtained at different radiation intensities, then the dynamic range and detection accuracy are improved, but the image processing complexity and computational requirements increase
Solution Approach 1:
The imaging process is segmented into multiple discrete steps, where images are captured at different radiation intensities (e.g., low, medium, high intensity). Each image captures a specific dynamic range portion, and the segments are later combined through processing to achieve comprehensive detection accuracy across the full dynamic range.
Solution Approach 2:
The patent introduces a new dimension to image capture by varying radiation intensity levels. Instead of capturing a single image at one intensity, the system captures multiple images across different intensity dimensions, then combines them to achieve superior detection accuracy that cannot be obtained from a single image.
2Area of stationary object
If multiple images are stitched together to form a composite image, then the coverage area and detection capability are improved, but alignment inaccuracies and processing time increase
Solution Approach 1:
The workpiece surface is segmented into multiple regions, each captured in a separate image. The system then stitches these segmented images together to form a comprehensive composite image of the entire workpiece surface, enabling detection across a larger area than a single image could capture.
Solution Approach 2:
The system performs preliminary actions by capturing multiple images at different radiation intensities and preparing them for stitching before final composite image generation. This preliminary processing enables efficient combination of images while maintaining alignment accuracy through pre-established coordinate systems and reference markers.
3Measurement precision
If high radiation intensity is used, then the signal strength and detection sensitivity are improved, but the risk of workpiece damage and hardware limitations increase
Solution Approach 1:
The detection process is segmented into multiple intensity levels, with low intensity images capturing subtle features without causing damage, medium intensity images providing baseline detection, and high intensity images capturing strong signals from prominent features. This segmentation allows the system to achieve high detection sensitivity while minimizing the risk of workpiece damage by not relying solely on high intensity radiation.
Solution Approach 2:
The system changes the radiation intensity parameter across multiple captures, obtaining images at different intensity levels. This parameter variation enables the system to detect features across a wide dynamic range while controlling the maximum intensity exposure to prevent workpiece damage, effectively decoupling detection sensitivity from damage risk.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the sensitivity and accuracy of defect detection and characterization of semiconductor workpieces by capturing a wide range of radiation intensities, improving image quality and reducing hardware-related inaccuracies.
Implementation Method 1
obtaining a plurality of images of at least a portion of a semiconductor workpiece, each of the plurality of images associated with exposing the at least a portion of the semiconductor workpiece to radiation at a different radiation intensity
Data Source
AI summary
An example method includes obtaining a plurality of images of at least a portion of a semiconductor workpiece. Each of the plurality of images associated with exposing the at least a portion of the semiconductor workpiece to radiation at a different radiation intensity. The example method includes generating a composite workpiece image of at least a portion of the semiconductor workpiece based at least in part on the plurality of images.