Object-Shadow Differentiation Using Convex Hull Region Selection
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Solution Overview
Problem
Conventional imaging technologies struggle to accurately differentiate objects from their shadows in imaged images, particularly under low-light or backlighting conditions where luminance values are similar, leading to inaccurate differentiation.
Innovation Solution
An information processing device and method that utilizes a feature region detection unit, first and second circumscribed polygon region calculation units, a principal axis of inertia calculation unit, and a region selection unit to divide and select convex hull circumscribed regions based on area ratios, enabling precise object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional luminance-based differentiation is used, then the processing is simple, but the object cannot be accurately differentiated from shadow under dark or backlighting conditions
Solution Approach 1:
The patent divides the feature region into multiple sub-regions using convex hull circumscribed regions and principal axis of inertia. By segmenting the detection process into multiple geometric analysis steps, the system achieves accurate object-shadow differentiation without relying solely on luminance thresholds, thereby resolving the contradiction between accuracy and complexity.
Solution Approach 2:
The patent transforms the differentiation approach from luminance-based parameter to geometric parameter-based (convex hull, principal axis of inertia). This parameter change enables accurate object differentiation under various lighting conditions by using shape characteristics rather than intensity values, achieving high accuracy without excessive processing complexity.
2Measurement precision
If geometric analysis with convex hull and principal axis is applied, then object differentiation accuracy improves, but processing complexity increases
Solution Approach 1:
The patent segments the geometric analysis into distinct steps: detecting feature region, calculating convex hull circumscribed region, determining principal axis of inertia, and dividing into sub-regions. This structured segmentation makes the complex geometric processing more manageable and efficient, achieving high accuracy without overwhelming complexity.
Solution Approach 2:
The patent performs preliminary geometric analysis by calculating convex hull and principal axis of inertia before final object differentiation. This preliminary action prepares the data in advance, making the subsequent differentiation process more efficient and accurate, thereby balancing complexity and precision.
Data Source
AI summary
Provided is an information processing device, an information processing method, and a computer-readable recording medium. A first circumscribed polygon region calculation unit calculates a first circumscribed polygon region as a convex hull circumscribed region that contains a feature region. A principal axis of inertia calculation unit calculates a principal axis of inertia for the feature region. A region division unit uses the principal axis of inertia to divide the feature region. On the basis of the area ratio of the two second circumscribed polygon regions and the first circumscribed polygon region as convex hull circumscribed regions that respectively contain the divided feature regions, a region selection unit selects either the first circumscribed polygon region or the two second circumscribed polygon regions. An object differentiation unit executes an object detection processing on the selected first circumscribed polygon region or two second circumscribed polygon regions.