Adaptive Focus Detection via Subject Pattern Recognition
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Solution Overview
Problem
Existing focus detection devices in cameras often fail to ensure accurate and efficient focus adjustment, particularly for certain types of subjects, due to limitations in phase difference detection methods.
Innovation Solution
A focus detection device comprising micro-lenses and light receiving elements in a two-dimensional array, where a focus detection unit detects phase differences and a recognition unit identifies subject image characteristics, allowing for optimal focus adjustment based on the recognized patterns, such as cyclical, edge, or gradation patterns, and adjusts the focus detection parameters accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed phase difference detection method is used, then the device structure is simple, but focus detection accuracy for certain subject patterns deteriorates
Solution Approach 1:
The patent implements dynamic adaptation of the phase difference detection method based on recognized subject patterns. The system switches between different detection algorithms (first method for cyclical patterns, second method for non-cyclical patterns) according to the detected subject characteristics, thereby improving focus detection accuracy without requiring multiple fixed detection systems.
Solution Approach 2:
The patent changes the detection parameters based on subject pattern recognition. When a cyclical pattern is detected, the system applies a specific phase difference detection method; when non-cyclical patterns are detected, a different method is applied. This parameter adaptation resolves the contradiction by optimizing detection accuracy for each pattern type while maintaining a unified detection system.
2Measurement precision
If pattern recognition and adaptive detection are implemented, then focus detection accuracy for different subjects is improved, but processing time increases
Solution Approach 1:
The patent performs pattern recognition on the subject image before executing the phase difference detection. By preliminarily identifying whether the subject has a cyclical or non-cyclical pattern, the system can select the appropriate detection method in advance, avoiding trial-and-error approaches and reducing overall processing time while maintaining high accuracy.
Solution Approach 2:
The patent segments the detection process into two distinct phases: pattern recognition phase and phase difference detection phase. This segmentation allows the system to apply different optimization strategies for each phase, with the pattern recognition enabling efficient selection of the appropriate detection algorithm, thereby balancing accuracy and processing time.
3Adaptability or versatility
If a single phase difference detection method is used, then the device complexity is low, but adaptability to different subject patterns deteriorates
Solution Approach 1:
The patent creates a universal detection system that can handle both cyclical and non-cyclical subject patterns through a single integrated apparatus. The system incorporates multiple detection methods within one device and selectively applies them based on pattern recognition, achieving multi-functionality without requiring separate dedicated systems for each pattern type.
Solution Approach 2:
The patent introduces pattern recognition as an intermediary process between image capture and phase difference detection. This intermediary analyzes subject characteristics and mediates the selection of the appropriate detection method, enabling the system to adapt to different subject patterns while maintaining a unified detection architecture rather than requiring multiple independent systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and efficient focus adjustment tailored to specific subject patterns, reducing false focus matches and improving focus detection speed and accuracy.
Implementation Method 1
a plurality of micro-lenses at which light fluxes having been transmitted through an image forming optical system enter
Data Source
AI summary
A focus detection device includes: a plurality of micro-lenses at which light fluxes through an image forming optical system enter, disposed in a two-dimensional array pattern; a plurality of light receiving elements disposed in correspondence to each of the plurality of micro-lenses; a focus detection unit that executes a detection of a defocus quantity of the image forming optical system by detecting, based upon outputs from the plurality of light receiving elements, a phase difference of a plurality of light fluxes through different areas of the image forming optical system; and a recognition unit that recognizes, based upon the outputs from the plurality of light receiving elements, characteristics of a subject image formed onto the plurality of light receiving elements via the plurality of micro-lenses, wherein: the focus detection unit detects the defocus quantity through a method optimal for the characteristics of the subject image recognized by the recognition unit.