Image Filtering Method for Orientation-Specific Edge Detection
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Solution Overview
Problem
Existing image filtering techniques fail to accurately detect edges in specific orientations, leading to suboptimal object recognition performance, as they do not replicate human-like recognition capabilities effectively.
Innovation Solution
An image filtering method that generates multiple images using filters along various channels, selects the channel with the maximum value for each image unit, and maintains consistency by filtering and comparing these images, incorporating lateral inhibition and inhibitory feedback to ensure accurate edge detection in specific orientations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing image filtering techniques are used to detect edges in specific orientations, then the filtering process can be performed, but the edge detection accuracy and consistency deteriorate
Solution Approach 1:
The patent applies feedback by comparing the selected channel from first images with channels from third images generated by filtering the second image, and adjusting values to maintain channel consistency. This feedback mechanism ensures that the edge detection remains consistent and accurate across different filtering stages.
Solution Approach 2:
The patent segments the image processing into multiple stages: generating first images by filtering the original image with filters along multiple channels, selecting a channel with maximum value for each image unit to create a second image, then generating third images by filtering the second image. This segmentation allows for systematic comparison and adjustment to maintain consistency.
2Adaptability or versatility
If filters are applied along multiple channels to detect edges in various orientations, then coverage of different orientations is improved, but processing complexity increases
Solution Approach 1:
The patent divides the filtering process into distinct stages: first filtering the original image to generate multiple first images along different channels, then selecting the maximum channel to create a second image, and finally filtering the second image to generate third images. This segmentation manages complexity by breaking down the multi-channel processing into manageable steps.
Solution Approach 2:
The patent applies filters along multiple channels (excessive action) to ensure comprehensive coverage of different orientations, then uses the maximum channel selection and comparison mechanism to refine the results. This approach ensures that all necessary orientations are covered while maintaining processing efficiency through selective retention of the maximum channel.
Data Source
AI summary
The present disclosure relates to an image filtering method for detecting an orientation component of an edge and an image recognizing method using the same. The image filtering method includes receiving an original image, generating a plurality of first images by filtering the original image with filters respectively generated along a plurality of channels, generating a second image by selecting a channel having a maximum value for each image unit, from the generated first images, and generating an output image whose edge is detected so as to maintain the consistency of channel by filtering the second image with filters respectively generated along the plurality of channels to generate a plurality of third images and comparing the channel of the second image with the channels of the third images.