Depth Camera Parcel Dimensioning for High-Throughput Measurement
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Solution Overview
Problem
Existing methods for obtaining accurate dimensions and weights of heterogeneous objects are time-consuming and tedious, often requiring manual measurements and lack high throughput capabilities.
Innovation Solution
A dimensioning system that includes a depth camera system and a computing device to automatically capture depth images, segment objects from the background, and compute dimensions, integrated with a scale for weight measurement, and optionally a barcode scanner for automated object identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement methods are used to capture object dimensions, then measurement accuracy can be achieved, but the process is time-consuming and reduces productivity
Solution Approach 1:
The patent replaces manual mechanical measurement tools (rulers, tape measures, calipers) with an automated depth camera system that captures three-dimensional spatial data. The camera system uses depth sensing technology to automatically measure object dimensions without physical contact, eliminating the need for manual operation while maintaining measurement accuracy and significantly increasing throughput.
Solution Approach 2:
The system creates a digital depth map copy of the object's three-dimensional shape. By capturing the object's spatial profile as a depth image and generating a digital representation, the system enables automated dimension extraction without physical measurement, allowing multiple measurements to be performed rapidly from the same digital model.
2Productivity
If automated depth camera systems are implemented, then productivity and speed are improved, but system complexity increases
Solution Approach 1:
The depth camera system is designed to perform multiple functions: capturing depth images, segmenting objects from backgrounds, calculating three-dimensional dimensions, and integrating with existing barcode scanning and scale systems. This multi-functional approach consolidates what would otherwise require separate devices into a single automated platform, managing complexity while enhancing productivity.
Solution Approach 2:
The system introduces a computing device as an intermediary that processes depth camera data, performs object segmentation, and calculates dimensions. This intermediary layer manages the complexity of data processing and provides a simplified interface between the depth camera hardware and the logistics software ecosystem, making the system easier to integrate and operate.
3Measurement precision
If object segmentation from background is performed, then measurement accuracy is improved, but processing time and computational requirements increase
Solution Approach 1:
The system performs preliminary object segmentation by identifying the object's spatial boundaries in the depth image before dimension calculation. By pre-processing the depth data to separate the object from the background using depth thresholding and contour detection, the system prepares clean measurement data in advance, ensuring accuracy while optimizing processing efficiency for the subsequent dimension extraction step.
Data Source
AI summary
A dimensioning system includes: a depth camera system mounted above a working surface; and a computing device including a processor and memory, the memory storing instructions that, when executed by the processor, cause the processor to: detect a triggering condition when an object is placed on the working surface; control the depth camera system to capture a depth image of the object in response to the triggering condition; segment the object from a background depicted in the depth image to identify a portion of the depth image corresponding to a segmented object; and compute a plurality of dimensions of the object based on the portion of the depth image.