Edge Detection Using Annular Aperture Mask
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Computers face challenges in detecting edges in images due to insufficient detail or contrast, which hinders the identification of objects and points of interest within images.
Innovation Solution
An edge detection method using an annular aperture generated by a circle drawing algorithm, where the image is scanned pixel-by-pixel to identify bisections that maximize intensity differences, determining the presence of edges by analyzing the angle of bisection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional edge detection methods are used on images with insufficient detail or contrast, then the computer can process the image, but the edge detection accuracy deteriorates
Solution Approach 1:
The patent segments the image processing into distinct operational phases: preprocessing to enhance contrast, followed by edge detection using the annular aperture mask method. This segmentation allows each phase to be optimized independently, improving overall edge detection accuracy on low-contrast images
Solution Approach 2:
The patent introduces an annular aperture mask as an intermediary element between the image data and the edge detection algorithm. This mask acts as a mediator that enhances the detection of edges in images with insufficient detail or contrast by filtering and emphasizing relevant features
2Measurement precision
If the image is processed pixel-by-pixel with annular aperture scanning, then edge detection precision is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary preprocessing of the image to enhance contrast and features before the main edge detection process. This preliminary action reduces the complexity of subsequent pixel-by-pixel analysis, thereby reducing overall processing time while maintaining accuracy
Solution Approach 2:
The patent applies the annular aperture mask at multiple overlapping positions across the image, performing more analyses than strictly necessary for minimal edge detection. This excessive action ensures comprehensive coverage and accurate edge localization, with the trade-off managed through efficient processing
Data Source
AI summary
An edge detection engine operates to scan an image to identify edges within the image. An annular aperture is used to locate the edges in the image. An output image is generated by the edge detection engine that identifies the locations of the edges found in the image.