Content-Aware Image Cropping via Edge Feature Distribution
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Solution Overview
Problem
Current image processing algorithms require human intervention for content-aware manipulations, which becomes costly and time-consuming when dealing with large sets of images, especially when adapting images for different display devices with varying aspect ratios.
Innovation Solution
The method involves determining the distribution of edge image features, using a convolution matrix to assign weights to pixels, and automatically cropping or overlaying text/images based on these weights to preserve the most details and adapt images to desired aspect ratios without human input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human input is used for content-aware image manipulations, then the quality and accuracy of image processing is improved, but the cost and time consumption increase significantly
Solution Approach 1:
The system performs self-service by automatically analyzing image content and making intelligent decisions about manipulations without human intervention. The algorithm independently determines cropping regions, overlay positions, and manipulation parameters by evaluating image features such as edges, corners, and content distribution, thereby eliminating the need for manual input while maintaining high processing quality
Solution Approach 2:
The patent replaces the mechanical system of human manual input with an automated computational algorithm. The system uses image processing techniques including edge detection, feature analysis, and content-based evaluation to substitute human decision-making with machine-based automated manipulation, achieving both speed and accuracy
2Productivity
If traditional batch image manipulation algorithms are used, then processing speed is improved, but the ability to preserve important image features deteriorates
Solution Approach 1:
The system applies local quality by analyzing different regions of the image independently and applying manipulations based on local content characteristics. Instead of uniform processing, the algorithm evaluates edge density, corner presence, and content importance in specific areas, then adjusts cropping and overlay operations locally to preserve important features while maintaining efficient batch processing
Solution Approach 2:
The patent dynamically changes processing parameters based on image content analysis. The algorithm adjusts cropping margins, overlay positions, and manipulation intensity according to detected features such as edge distribution and content density, allowing flexible adaptation to different image types while preserving important features and maintaining processing efficiency
3Adaptability or versatility
If images are cropped to fit different aspect ratios, then adaptability to display devices is improved, but the preservation of important image details may be compromised
Solution Approach 1:
The system performs preliminary action by pre-analyzing image content and identifying important features such as edges, corners, and key objects before cropping. This advance evaluation allows the algorithm to determine optimal cropping regions that maintain aspect ratio compatibility while preserving critical image details, preventing information loss before the actual cropping operation
Data Source
AI summary
A method in a computing device for performing intelligent weighted image manipulations is described. The method includes determining whether edge image features are distributed evenly across an image. When the edge image features in the image are not distributed evenly across the image, the method further includes cropping the image at the bounds of an overlay region of a desired size that is set at a position within the image to include a largest number of the edge image features. According to an embodiment, when the edge image features in the image are distributed evenly across the image, the method further includes cropping the image at the bounds of the overlay region of a desired size that is set at the center of the image.