Batch Image Resizing with Aspect Ratio Matching
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Solution Overview
Problem
Existing image processing systems can only resize one image at a time, requiring users to perform repetitive operations for multiple images, which is cumbersome and inefficient.
Innovation Solution
An image processor that allows users to select and resize multiple images collectively based on predefined resizing conditions, aspect ratios, and storage criteria, using a control section and image processing section to apply uniform resizing to images with different sizes and aspect ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If one image is resized at a time, then the resizing processing can be performed accurately on each image, but the operation becomes troublesome and time-consuming when multiple images need to be resized
Solution Approach 1:
The patent merges multiple individual resizing operations into a single batch processing operation. The control section reads multiple image files from storage, applies resizing processing to all of them simultaneously using the same resizing conditions, and writes the resized images back to storage. This combining of operations eliminates the need for repeated manual intervention and significantly reduces the time required to resize multiple images.
Solution Approach 2:
The system performs preliminary actions by pre-defining multiple sets of resizing conditions (such as different target sizes, aspect ratios, and quality settings) before the actual resizing operation. The user can select from these pre-configured conditions, and the system automatically applies the appropriate set to each image in the batch, eliminating the need for repeated configuration during the resizing process.
2Productivity
If multiple images are resized collectively, then the processing efficiency is improved, but the system complexity increases due to handling different aspect ratios and sizes
Solution Approach 1:
The patent handles different image parameters (aspect ratios, sizes, resolutions) by automatically detecting the parameters of each input image and selecting or adjusting the appropriate resizing conditions from the pre-defined sets. The control section reads image metadata to determine aspect ratios and dimensions, then applies the correct transformation parameters to each image, managing complexity through automated parameter matching rather than manual configuration.
Solution Approach 2:
The resizing system is designed with multi-functionality to handle various image formats, aspect ratios, and size requirements through a single unified processing framework. The control section can process different types of images (photos, thumbnails, various resolutions) using the same batch processing mechanism, making the system universally applicable to diverse image resizing needs without requiring separate processing paths for each image type.
3Ease of operation
If automatic resizing is performed without user selection, then the operation becomes simpler, but the user cannot control which images are resized or what resizing conditions to apply
Solution Approach 1:
The system provides dynamic control options that adapt to user needs. The user can dynamically select which images to include in the batch processing (by specifying file names, patterns, or date ranges) and dynamically choose from multiple pre-defined resizing condition sets. This dynamic selection capability allows the system to balance automation with user control, making it both easy to operate and adaptable to different resizing scenarios.
Solution Approach 2:
The system enables self-service by allowing users to configure resizing conditions once and then automatically apply them to multiple images without further intervention. The control section automatically reads image files, applies the selected resizing conditions, and saves the results, performing the bulk of the work autonomously while still allowing initial user direction for image selection and condition choice.
Data Source
AI summary
An image processor that can get a number of image files resized collectively is provided in order to realize a more user-friendly resizing function.The image processor includes: a control section configured to select a particular set of resizing conditions from a plurality of sets of resizing conditions in accordance with a user's instruction; and an image processing section configured to perform resizing processing on each of a plurality of images in accordance with the selected particular set of resizing conditions. Each set of resizing conditions specifies a plurality of estimated resized image sizes. Each estimated resized image size is associated with a respective image aspect ratio. For said each of the plurality of images to be resized, the image processing section selects an estimated resized image size from the selected particular set of resizing conditions according to the aspect ratio of said each of the plurality of images and performs the resizing processing on said each of the plurality of images in accordance with the selected estimated resized image size.