Open Carton Box Dimensioning Using Depth Data and Flap Detection
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Solution Overview
Problem
Existing systems are limited to measuring closed carton boxes and cannot efficiently compute dimensions of open carton boxes, especially when multiple boxes are present, leading to time-consuming and error-prone manual measurements.
Innovation Solution
Utilizing depth sensors to capture data points from open carton boxes, clustering these points to identify flaps, determining a cross section, and estimating a minimum bounding rectangle to calculate dimensions automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement of carton boxes is used, then measurement accuracy can be maintained, but time consumption increases significantly
Solution Approach 1:
The patent replaces manual mechanical measurement with an automated depth sensor-based measurement system. The depth sensor captures depth data points of the carton box, and a processor automatically computes dimensions by identifying flaps, determining cross-sections, and calculating bounding rectangles, eliminating manual intervention while maintaining measurement accuracy.
Solution Approach 2:
The measurement system performs self-service by automatically capturing depth data, processing the data to identify carton box features, and computing dimensions without human intervention. The system independently completes the entire measurement process, from data acquisition to dimension calculation.
2Adaptability or versatility
If existing dimension computation systems are used, then closed carton boxes on conveyor belts can be measured, but open carton boxes and multiple boxes cannot be measured simultaneously
Solution Approach 1:
The measurement system achieves universality by being capable of measuring both closed and open carton boxes, as well as multiple boxes simultaneously. The depth sensor captures data for all boxes in the scene, and the processing algorithm identifies and measures each box independently based on its geometric features, providing a versatile measurement solution.
Solution Approach 2:
The patent applies segmentation by dividing the measurement scene into individual carton box instances. The system identifies separate boxes, their flaps, and cross-sections independently, allowing simultaneous measurement of multiple boxes. Each box is processed as a distinct entity through the dimension computation algorithm.
3Productivity
If automated depth sensor measurement is implemented, then measurement speed and multi-box capability improve, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary processing layer between the depth sensor and the measurement results. The processor acts as a mediator that receives raw depth data points, applies geometric processing to identify flaps and cross-sections, and computes final dimensions. This intermediary layer manages the complexity of automated measurement while enabling high-speed multi-box capability.
Data Source
AI summary
Embodiments of present disclosure relates to method and dimension determination system for determining dimensions of carton box. The dimension determination system receives plurality of datapoints associated with open carton box. The dimension determination system extracts depth datapoints from plurality of datapoints for identifying plurality of flaps. The dimension determination system determines height of open carton box using depth datapoints. The dimension determination system generates contour and estimates rectangle figure for contour of open carton box. Further, the dimension determination system determines width and length by extracting vertices of rectangle figure. Thereafter, the dimension determination system utilises width, length and height to obtain dimensions of open carton box. Thus, the present disclosure automatically determines dimensions of carton box.