Box Dimension Estimation Using Geometric Mark Detection
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Solution Overview
Problem
Most imaging systems lack the capability to estimate the volume or dimensions of a box object from captured images, requiring additional equipment for size determination.
Innovation Solution
An imaging system that captures images of a box object using an imaging sensor and processes corner points and geometric marks to calculate the volume and dimensions, including length, width, and height, through image processing algorithms and calibration matrices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging systems are used to capture images of a box object, then image capture is achieved, but the system lacks the capability to estimate volume or dimensions
Solution Approach 1:
The imaging system is enhanced to perform multiple functions: capturing images and automatically estimating box dimensions and volume. The system integrates image processing algorithms that detect corner points, calculate geometric parameters, and derive dimensional information from standard imaging components, making the system universal for both imaging and measurement tasks.
Solution Approach 2:
The imaging system performs self-measurement by automatically processing captured images to extract dimension information. The system uses its own captured images as input for dimension estimation, eliminating the need for separate measurement tools or external intervention, thus serving itself for both imaging and measurement purposes.
2Ease of operation
If separate measurement tools are used to determine box dimensions, then accurate measurement is achieved, but convenience is reduced
Solution Approach 1:
The imaging system merges the functions of image capture and dimension measurement into a single integrated system. By combining the imaging sensor, processing algorithms, and measurement capabilities, the system eliminates the need for separate measurement tools, reducing the quantity of equipment required while maintaining measurement accuracy.
Solution Approach 2:
The imaging system is designed to perform multiple functions including image capture, corner point detection, and dimension estimation. This multi-functional approach allows a single device to replace multiple specialized tools, improving operational convenience by reducing the number of tools users need to handle and coordinate.
3Measurement precision
If image processing algorithms are implemented to estimate dimensions, then measurement capability is added, but processing complexity increases
Solution Approach 1:
The dimension estimation process is segmented into distinct processing stages: corner point detection, geometric parameter calculation, and volume computation. Each stage processes specific aspects of the image data independently, breaking down the complex measurement task into manageable segments that can be processed systematically, thereby managing algorithmic complexity while maintaining accuracy.
Solution Approach 2:
The system performs preliminary actions by first detecting corner points and establishing geometric relationships before calculating final dimensions. This preliminary processing of key feature points simplifies subsequent dimension calculations, as the critical reference points are identified in advance, reducing the complexity of the overall measurement algorithm.
Data Source
AI summary
A method to determine the volume of a box object from the captured image of the box object. The method includes identifying a geometric mark on the box object in the captured image to find the positions of two reference points of the geometric mark. The two reference points are separated by a predetermined distance. The method also includes processing a group of parameters and a predetermined mapping obtained from a calibration process. The group of parameters includes the positions of the two reference points and the predetermined distance separating the two reference points.