Electronic Camera Object Detection via Color-Based Tonality Correction
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Solution Overview
Problem
Conventional electronic cameras are limited in their ability to detect objects other than human faces, as they do not adjust exposure and tonality correction effectively for non-human subjects, leading to suboptimal image capture.
Innovation Solution
An electronic camera system that includes an imager, an extractor to identify specific reference images, an adjuster to adjust exposure, an identifier to determine object colors, and a corrector to adjust tonality, allowing for improved detection and capture of non-human objects by emphasizing specific areas and correcting tonality based on identified colors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the camera is designed to detect human faces only, then the detection capability for human faces is high, but the detection capability for other objects is limited
Solution Approach 1:
The camera system is designed to perform multiple detection functions - it can detect human faces using traditional methods and also detect other objects (animals, inanimate objects) using color-based identification. The identifier unit determines object types by analyzing color information from different regions, enabling the single camera system to handle diverse detection tasks without requiring separate specialized detection systems for each object type.
2Manufacturing precision
If exposure adjustment emphasizes a predetermined area, then image quality for that area is improved, but processing time increases
Solution Approach 1:
The adjuster unit applies different exposure adjustments to different regions of the image based on local requirements. By identifying the object type and its location, the system can emphasize exposure adjustment for the area containing the detected object while using standard exposure for other regions, thereby improving image quality where needed without unnecessarily increasing processing time for the entire image.
Solution Approach 2:
The system performs preliminary object identification and location determination before final exposure adjustment. By pre-identifying the object type and its position in the scene, the camera can prepare targeted exposure parameters in advance, reducing the time required for final image processing and optimization.
3Manufacturing precision
If tonality correction is applied to the entire scene image, then overall image quality is improved, but processing complexity increases
Solution Approach 1:
The corrector unit applies tonality correction selectively based on the identified object type and its location. Rather than uniformly processing the entire scene image, the system tailors tonality correction parameters to match the specific object being detected (e.g., different corrections for animals vs. inanimate objects), thereby improving image quality for the detected subject while reducing unnecessary processing complexity for the rest of the scene.
Data Source
AI summary
An electronic camera includes an imager, having an imaging surface capturing a scene, which repeatedly outputs a scene image. An extractor extracts a specific reference image coincident with a partial image outputted from the imager corresponding to a predetermined area allocated to the imaging surface, from among a plurality of reference images. An adjuster executes a process of adjusting an exposure amount by emphasizing the predetermined area in parallel with the extraction process. An identifier identifies a color of an object equivalent to the partial image, corresponding to extracting the specific reference image. A corrector executes a process of correcting a tonality of the scene image with reference to the identified result, in place of the extraction process. A searcher searches for a partial image coincident with the specific reference image from the scene image having the corrected tonality.