Multi-Angle Container Imaging for Barcode and Feature Verification
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Solution Overview
Problem
Existing container placement devices require frequent adjustments of camera position or focal length to capture images of containers due to differences in the image capturing position must be frequently adjusted or the camera focal length must be adjusted to maintain a better image capturing result. In addition, the contents of the container may be toxic and, when the camera leaks out, resulting in a safety risk. In addition, the contents of the container may be toxic and, when the camera is used to capture images of containers due to the toxic and, when the camera is used to capture images of containers due to the toxic and, when the camera is used to capture images of containers, which poses a safety risk and inefficiency in image capturing.
Innovation Solution
An image recognition system with an image capturing subsystem that includes a rack assembly with rotating carriers, an image capturing component, and modules for barcode and feature recognition, allowing for multiple angle image capture without adjusting the camera position, and a comparison module to verify recognition results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the camera position or focal length is adjusted to capture images of containers at different positions, then the image capturing quality is improved, but the time consumption and operational complexity increase
Solution Approach 1:
The patent transitions from a single fixed camera position to a multi-dimensional imaging approach by introducing multiple cameras positioned at different locations (front, rear, left, right sides of the rack). This spatial dimensionality change allows simultaneous capture of containers at various positions without requiring camera adjustment, thereby improving image quality while eliminating time loss from repositioning.
Solution Approach 2:
The system employs adjustable and rotatable camera mounts that enable dynamic positioning of cameras. The cameras can be rotated and adjusted to optimal angles for capturing containers at different rack positions, maintaining high image quality adaptability without manual intervention for each container position change.
2Ease of operation
If workers manually refill container materials, then the operation flexibility is maintained, but safety risks increase due to potential toxic gas leakage
Solution Approach 1:
The system implements automated container identification and recognition through image capture and processing algorithms. The computer automatically identifies container types, positions, and contents based on captured images, eliminating the need for workers to manually handle or inspect containers, thus maintaining operational flexibility while removing workers from hazardous environments.
Solution Approach 2:
The patent introduces an automated image recognition system as an intermediary between the containers and the control system. This intermediary automatically processes container information through image analysis, replacing direct human interaction with containers and eliminating exposure to toxic substances while preserving operational control.
3Device complexity
If a single camera is used to capture container images, then the device simplicity is maintained, but the recognition accuracy decreases due to limited viewing angles
Solution Approach 1:
The imaging system is segmented into multiple independent camera units, each responsible for capturing images from specific rack positions (front, rear, left, right sides). This segmentation allows each camera to focus on a specific viewing angle with optimized positioning, improving recognition accuracy for containers at different locations while keeping individual camera units simple and manageable.
Solution Approach 2:
The multiple cameras collectively provide universal coverage of all rack positions and container types. Each camera is designed with multi-functional capability to capture various container orientations and positions, ensuring comprehensive recognition accuracy across different scenarios without requiring complex individual camera systems.
Data Source
AI summary
An image recognition system for recognizing a plurality of containers includes an image capturing component, a barcode recognition module, a container feature recognition module and a comparison module. The image capturing component is used to acquire a plurality of images, wherein each of the plurality of images includes a picture of the plurality of containers at a different angle. The barcode recognition module is used to acquire a first comparison result by recognizing barcodes on the plurality of containers in the plurality of images. The container recognition module is used to acquire a second comparison result by recognizing appearance features of the plurality of containers in the plurality of images. The comparison module is used to generate a final comparison result by comparing the first comparison result with the second comparison result.