Eyelid Detection Using Sobel Edge Extraction
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Solution Overview
Problem
Existing eyelid detection techniques are inefficient due to high processing times and costs, particularly when implemented on low-speed in-vehicle CPUs, and require extensive calculations.
Innovation Solution
An eyelid detection apparatus and method that uses a Sobel filter-based approach to minimize calculations by extracting edge lines and calculating eyelid candidates based on specific thresholds and patterns, enabling efficient detection of eyelid positions in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If template matching with correlative operation is used for eyelid detection, then detection accuracy is improved, but processing time increases and becomes unsuitable for low-speed in-vehicle CPUs
Solution Approach 1:
The patent segments the eyelid detection process into distinct stages: edge line extraction using Sobel filter, candidate line selection based on geometric constraints, and final verification. This segmentation allows each stage to use optimized algorithms appropriate to its specific task, reducing overall processing time while maintaining accuracy
Solution Approach 2:
The patent extracts only the essential features needed for eyelid detection (edge lines and their geometric relationships) rather than performing full template matching. By extracting and processing only critical information, the system achieves fast detection suitable for low-speed CPUs without sacrificing detection accuracy
2Speed
If dedicated computing units are used for eyelid detection, then processing speed is improved, but system cost increases
Solution Approach 1:
The patent designs the eyelid detection algorithm to be universally applicable on general-purpose CPUs without requiring dedicated hardware accelerators. The algorithm uses basic arithmetic operations and simple logical comparisons that can be efficiently executed on any standard processor, making the system cost-effective while maintaining real-time processing capability
Solution Approach 2:
The patent replaces complex mechanical/computational systems (dedicated computing units) with a streamlined software-based algorithm that uses minimal calculations. The Sobel filter-based edge detection and geometric constraint methods achieve fast processing through algorithmic efficiency rather than hardware power, reducing system cost and complexity
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
The solution significantly reduces processing time and costs by accurately detecting eyelid positions with minimal calculations, making it suitable for low-speed CPUs, such as those in vehicles.
Implementation Method 1
the Sobel filter, a first example of an edge-line extracting means, is used to extract edge lines
Data Source
Figure 1
Figure 2
Figure 3A~3F
AI summary
An eyelid detection apparatus (50) includes a face-image storing apparatus (22) for storing an image of a face of a subject, an eyelid-candidate extracting apparatus (24) for processing the image stored in the face-image storing apparatus (22) to extract a pair of lines, which becomes a candidate of a combination of a line corresponding to an upper eyelid and a line corresponding to a lower eyelid, a parameter calculating apparatus (24) for calculating a parameter, which indicates a possibility that a part of the image stored in the face-image storing apparatus (22), the part corresponding to the pair of lines extracted by the eyelid-candidate extracting apparatus (24), includes at least one of outer and inner corners of an eye, and an eyelid detecting apparatus (24) for detecting a position of an eyelid of the subject on the basis of the parameter calculated by the parameter calculating apparatus (24).