Semiconductor Array Identification via Correlation Analysis
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Solution Overview
Problem
Current examination processes for semiconductor wafers during fabrication struggle to accurately distinguish between arrays with repetitive structural elements and surrounding regions with different features, leading to inefficiencies in defect detection and classification.
Innovation Solution
A system utilizing a processor and memory circuitry performs correlation analysis on pixel intensity between an image of a semiconductor specimen and a reference image, clusters sub-areas based on distance criteria, and outputs data to distinguish between arrays and regions, enabling precise identification and correction of distortions in the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated examination processes are used to detect defects on semiconductor specimens, then productivity and defect detection capability are improved, but the ability to accurately distinguish between arrays with repetitive structural elements and surrounding regions deteriorates
Solution Approach 1:
The image processing system divides the semiconductor specimen image into distinct segments: arrays with repetitive structural elements and surrounding regions with different features. By segmenting the image based on correlation analysis results, the system can apply different processing rules to each segment, thereby maintaining high productivity while improving the accuracy of distinguishing between arrays and surrounding regions.
Solution Approach 2:
The patent introduces correlation analysis as an intermediary mechanism between the raw image data and the final defect classification. This intermediary process computes correlation values that serve as a bridge, enabling the system to accurately differentiate between arrays and surrounding regions even in automated high-speed examination, thus resolving the contradiction between productivity and measurement precision.
2Reliability
If correlation analysis is performed on the entire image, then comprehensive defect detection is achieved, but processing time and computational complexity increase
Solution Approach 1:
The system segments the image processing task by first identifying array regions through correlation analysis and then treating array regions and surrounding regions differently. This segmentation allows the system to maintain comprehensive defect detection while reducing overall processing time by applying simplified processing to certain regions.
Solution Approach 2:
The patent applies partial action by performing full correlation analysis only where necessary (at region boundaries or where defects are suspected) rather than uniformly across the entire image. This approach maintains detection reliability while significantly reducing processing time and computational resources required.
Data Source
AI summary
There is provided a method and a system configured obtain an image of a semiconductor specimen including one or more arrays, each including repetitive structural elements, and one or more regions, each region at least partially surrounding a corresponding array and including features different from the repetitive structural elements, wherein the PMC is configured to, during run-time scanning of the semiconductor specimen, perform a correlation analysis between pixel intensity of the image and pixel intensity of a reference image informative of at least one of the repetitive structural elements, to obtain a correlation matrix, use the correlation matrix to distinguish between one or more first areas of the image corresponding to the one or more arrays and one or more second areas of the image corresponding the one or more regions, and output data informative of the one or more first areas of the image.