Object and Saliency Guided Image Cropping With Template Layering
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Solution Overview
Problem
Manual image processing for propaganda is inefficient and labor-intensive, requiring manual cropping and addition of information, which lacks efficiency and effectiveness.
Innovation Solution
An image processing method involving target object detection, saliency detection, cropping based on detection results, and adding layer information based on an image template to automatically generate target images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual post-production processing is performed on original images, then image applicability for propaganda is ensured, but processing efficiency is extremely low and labor intensity is high
Solution Approach 1:
The system enables automatic image processing where the computer executes detection, cropping, and composition operations without human intervention. Object detection algorithms automatically identify key elements, saliency detection algorithms determine important regions, and the system automatically crops and composes images according to propaganda requirements, replacing manual post-production work
Solution Approach 2:
Manual mechanical operations (hand cropping, manual composition) are replaced by automated computational systems. The patent employs object detection algorithms, saliency detection algorithms, and automated image processing software to substitute human operators, achieving both high efficiency and maintained image quality
2Manufacturing precision
If manual cropping and information addition are performed, then targeted propaganda images are obtained, but the process is labor-intensive and time-consuming
Solution Approach 1:
The system performs preliminary detection and analysis before actual image processing. Object detection algorithms pre-identify key objects and their positions, saliency detection algorithms pre-determine important regions, and the system prepares cropping schemes in advance, enabling rapid execution of the actual processing operations
Solution Approach 2:
The system dynamically adjusts processing parameters based on detected image features. Cropping ratios, composition layouts, and information placement positions are automatically optimized according to the specific characteristics of each image, maintaining high processing quality while reducing time consumption through parameter optimization
Data Source
AI summary
An image processing method includes: performing target object detection on an initial image to obtain an object detection result, and performing image saliency detection on the initial image to obtain a saliency detection result; cropping the initial image based on the object detection result and the saliency detection result to obtain a corresponding cropped image; acquiring an image template for indicating an image style, and acquiring layer information corresponding to the image template; and adding the layer information to the cropped image based on the image template to obtain a target image corresponding to the image style indicated by the image template.