Image Processing Apparatus Face Composition Trimming
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Solution Overview
Problem
Users are often dissatisfied with the quality of captured images due to poorly detected or positioned faces, which affects the composition and focus of digital images.
Innovation Solution
An image processing method and apparatus that detects faces, determines image composition based on face position, size, and number, and generates a second image by trimming the first image to improve face quality, including post-processing for clarity and user editing options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If face detection function is included in digital image-capturing apparatus, then functions and information regarding detected faces are provided to users, but the quality of captured images may not be satisfactory because faces in images may not be of high enough quality
Solution Approach 1:
The system performs preliminary face detection and composition analysis on the captured image, then proactively generates a trimmed second image with optimized face positioning and size before the user views or uses the image. This preliminary processing ensures high face quality is achieved in advance, preventing user dissatisfaction.
Solution Approach 2:
The system extracts the detected face from the original captured image and creates a separate trimmed image (second image) that contains only the essential portion with the face at optimal composition. This extraction isolates the face quality issue from the rest of the image, allowing dedicated optimization of face presentation.
2Manufacturing precision
If automatic trimming is performed based on face detection, then face quality and composition are improved, but additional processing time and computational resources are required
Solution Approach 1:
The system performs partial processing by generating only a trimmed second image when face detection quality is insufficient, rather than processing all captured images. This selective approach applies trimming only when needed, reducing overall processing time while still improving face quality in problematic cases.
Solution Approach 2:
The trimming operation is performed as a preliminary step immediately after face detection, using the detected face position and size information to quickly generate the optimized second image. This preliminary trimming avoids subsequent time-consuming manual editing or re-shooting.
3Adaptability or versatility
If multiple faces are detected, then the system can handle complex scenes, but determining optimal composition becomes more difficult
Solution Approach 1:
The system segments the multiple detected faces into individual face regions, analyzing each face's position, size, and importance separately. This segmentation allows the composition determination unit to evaluate different trimming options for each face or combination of faces, managing complexity by breaking down the multi-face composition problem into manageable segments.
Solution Approach 2:
The system changes composition parameters (such as crop boundaries, aspect ratio, and face size in frame) based on the number and arrangement of detected faces. When multiple faces are detected, the system adjusts these parameters to optimize the inclusion and presentation of multiple subjects, transforming the composition to suit multi-face scenarios.
Data Source
AI summary
A method of processing an image involves detecting a face from a first image; determining a composition of the first image; selecting a composition of a second image according to the composition of the first image; and generating the second image including the face by trimming the first image, according to the composition of the second image.