Neural Mosaic Image Generation Without Source Image Libraries
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Solution Overview
Problem
Existing methods require a base image and source images to construct a mosaic image, limiting their applicability when neither is available.
Innovation Solution
A computing apparatus and method that generates a mosaic image using a neural network to create source images from an input image without relying on a base image or source images, incorporating features like color, texture, and geometric information, and evaluates esthetics for natural and user-desired composition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional mosaic construction methods are used requiring base image and source images, then the mosaic construction process is simple and straightforward, but the applicability is limited when neither base image nor source images are available
Solution Approach 1:
The system enables self-service by allowing the base image to generate source images automatically through neural network processing. The base image is divided into multiple regions, and source images are synthesized from these regions without requiring external source image inputs, making the system adaptable to scenarios where no pre-existing source images are available.
Solution Approach 2:
A neural network serves as an intermediary component between the base image and the generated source images. The neural network processes the base image regions and transforms them into suitable source images, enabling the mosaic construction process to function without direct human intervention or pre-prepared source images.
2Adaptability or versatility
If source images are generated from base image regions using neural network, then the applicability without source images is improved, but the computational complexity and processing time increase
Solution Approach 1:
The base image is segmented into multiple smaller regions, and the neural network processes each region independently to generate corresponding source images. This segmentation approach reduces the computational burden compared to processing the entire base image at once, while still enabling source image generation without pre-existing source images.
3Ease of operation
If manual selection and arrangement of source images is used, then the composition control is precise, but the time consumption and labor requirements increase
Solution Approach 1:
The system performs self-service by automatically generating and arranging source images based on the base image regions. The neural network synthesizes source images and the system automatically positions them in the mosaic grid, eliminating the need for manual selection and arrangement operations, thus reducing both time consumption and operational complexity.
Data Source
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AI summary
Provided are a computing apparatus for constructing a mosaic image and an operation method of the same. The computing apparatus includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to: segment an input image into a plurality of sub areas to obtain a plurality of sub area images, extract a feature from each of the plurality of sub area images, generate a plurality of source images respectively corresponding to the plurality of sub areas using an image generation neural network, the image generation neural network using, as a condition, the feature extracted from each of the plurality of sub area images, and combine the plurality of source images respectively corresponding to the plurality of sub areas to generate a mosaic image.a