Content-Aware Image Region Resizing via Segmentation
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Solution Overview
Problem
Existing image resizing techniques, such as standard scaling and seam carving, are inadequate as they fail to consider image content and often result in artifacts or distortions, especially when resizing images for different devices or resolutions.
Innovation Solution
A content-aware resizing method that applies different resizing techniques to various regions of an image based on local content, using techniques like seam carving, scaling, or hybrids, to achieve a specified target size or aspect ratio while minimizing visual artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard image scaling is applied uniformly to the entire image, then the image can be resized to fit different displays, but it results in various artifacts or distortions of the input image
Solution Approach 1:
The image is divided into multiple regions based on content importance. Different resizing techniques are applied to different regions: content-aware seam carving is applied to important regions to preserve quality, while standard scaling is applied to less important regions. This segmentation allows the system to achieve both adaptability and quality preservation.
Solution Approach 2:
Different quality levels are applied to different parts of the image based on their importance. Important content regions maintain high quality through seam carving, while peripheral or less important regions use standard scaling. This local differentiation resolves the contradiction by making quality adaptive to content importance.
2Manufacturing precision
If seam carving techniques are applied to resize images by removing or adding pixels, then content-aware resizing can be achieved, but it may be computationally expensive and produce undesirable artifacts or distortions
Solution Approach 1:
The image is segmented into important and less important regions. Seam carving is applied only to important regions where it provides significant quality improvement, while standard scaling handles less important regions. This reduces overall computational complexity while maintaining content-aware quality where it matters most.
Solution Approach 2:
Instead of applying seam carving to the entire image (excessive action), the technique is applied partially only to important regions. This partial application reduces computational cost while still achieving the benefits of content-aware resizing for the most critical parts of the image.
3Ease of operation
If cropping is used to resize images by removing pixels from the periphery, then the image can be resized, but it can only remove pixels from the image periphery and is of limited use
Solution Approach 1:
The image is divided into multiple regions with different resizing strategies. While cropping can be applied to peripheral regions, important content regions use seam carving or other content-aware techniques. This segmentation makes the overall system more versatile than simple cropping alone.
Solution Approach 2:
The resizing system uses a composite approach, combining multiple resizing techniques (cropping, seam carving, standard scaling) applied to different regions. This composite strategy achieves both the simplicity of cropping and the versatility of content-aware methods.
Data Source
AI summary
A system and method for expansion and reduction of images may apply resizing techniques independently to different regions of an input image to produce a resized version of the image having a specified target size and/or ratio. A content-aware resizing technique may be applied to some regions of the image. Each region may be reduced or expanded by the same amount based on local content, or different regions may be resized by different amounts to meet a resizing target for the input image. The same resizing technique may be applied to each region, or different resizing techniques may be applied to different regions. A given region or unselected portion of the image may not be resized at all. The techniques may be implemented by program instructions of an image editing application, and the definition of the regions and/or the selection of locally applied techniques may be configurable by a user.