Image Processing Apparatus for Selective Album Extraction
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Solution Overview
Problem
Existing image processing methods for creating albums or index printing often extract unsatisfactory images when the number of good images is insufficient, leading to the inclusion of 'failure images' with issues like underexposure, poor color balance, or blurring.
Innovation Solution
An image processing apparatus that classifies images into high and low user satisfaction groups, extracting images with minor dissatisfaction factors from the lower satisfaction group when the specified number of high satisfaction images is not met, ensuring only images with relatively high user satisfaction are selected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If images are automatically extracted when the number of user-selected images is insufficient, then the album can be completed, but failure images with dissatisfaction factors may be included
Solution Approach 1:
The patent segments the image selection process into multiple stages: first extracting images without dissatisfaction factors, then separately handling failure images with dissatisfaction factors. This segmentation allows the system to prioritize high-quality images while still utilizing lower-quality images when necessary, thus resolving the contradiction between productivity and reliability.
Solution Approach 2:
The patent applies local quality by differentiating between images with and without dissatisfaction factors, and further categorizing failure images by the severity and type of their dissatisfaction factors. This allows selective extraction based on local image quality characteristics, ensuring that only acceptable failure images are included when needed.
2Quantity of substance
If all images are extracted to meet the user-specified number, then the album is complete, but the quality of extracted images deteriorates
Solution Approach 1:
The patent performs preliminary classification of images into those without dissatisfaction factors and failure images with dissatisfaction factors before extraction. This preliminary action enables the system to first extract high-quality images and then selectively add lower-quality images only when the user-specified number is not reached, maintaining quality standards while meeting quantity requirements.
Solution Approach 2:
The patent changes the selection parameter from a binary acceptable/unacceptable criterion to a multi-level classification based on dissatisfaction factor types and severity. This parameter change allows flexible adjustment of extraction criteria to balance quantity and quality based on user needs.
3Device complexity
If automatic extraction is performed without classification, then processing is simple, but the extracted images may include apparent failure images
Solution Approach 1:
The patent segments the image group into classified categories based on dissatisfaction factors, creating a structured extraction process that first handles high-quality images and then selectively handles failure images. This segmentation adds classification complexity but significantly improves reliability by preventing apparent failure images from being extracted.
Data Source
AI summary
Provided is an image processing apparatus configured to preferentially extract an image with high user satisfaction when multiple images are automatically extracted from an image group. A user specifies the number of images to be extracted from the image group. The image group is classified into a first image group with high user satisfaction and a second image group with low user satisfaction. When the number of images extracted from the first image group does not reach the specified number, an image having only a dissatisfaction factor acceptable to the user is additionally extracted.