Handheld Scanner Image Assembly via Coarse Fine Positioning
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Solution Overview
Problem
Handheld scanners face challenges in accurately assembling successive outputs of an image array into a composite image without mechanical constraints, often resulting in poor image quality due to inaccurate navigation sensors and inefficient image processing techniques.
Innovation Solution
A method and system that determine the relative position of each image frame to form a composite image by combining image frames captured while moving a handheld scanner over an object, using both coarse and fine positioning techniques to improve image quality and user feedback during scanning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If mechanical constraints are removed to enable handheld scanning flexibility, then ease of operation is improved, but image assembly accuracy deteriorates
Solution Approach 1:
The patent replaces mechanical constraints with a computational approach. Instead of physically constraining the handheld scanner to move along predefined paths, the system uses image processing algorithms to determine the relative positions of successive image frames and assemble them into an accurate composite image, thereby eliminating the need for mechanical guidance mechanisms.
Solution Approach 2:
The patent introduces navigation sensors and image processing software as intermediary systems between the handheld scanner and the final composite image. These intermediaries track the scanner's position and orientation, and computationally align the image frames, serving as a bridge that enables flexible handheld operation while maintaining assembly accuracy.
2Extent of automation
If navigation sensors are used to track scanner position, then image assembly capability is enabled, but measurement precision deteriorates due to sensor inaccuracies
Solution Approach 1:
The patent employs feedback mechanisms where the system continuously monitors the position and orientation of the scanner through navigation sensors, compares this information with the actual image content, and adjusts the alignment of successive frames accordingly. This feedback loop compensates for sensor inaccuracies by using the visual information itself to correct positioning errors.
Solution Approach 2:
The patent changes the parameters used for position determination from relying solely on navigation sensor data to incorporating image-based feature matching and recognition. By analyzing visual features, edges, and patterns in the images themselves, the system can refine position estimates and overcome the limited precision of navigation sensors.
3Productivity
If successive image frames are assembled into composite images, then scanning capability is achieved, but processing time increases
Solution Approach 1:
The patent divides the image assembly process into segments, processing and aligning successive image frames in a sequential manner as the scanner moves across the document. Rather than capturing all images first and then processing them, the system processes images in real-time during scanning, dividing the overall task into smaller, manageable units that can be handled efficiently.
Solution Approach 2:
The patent performs preliminary actions by pre-processing navigation sensor data and image frames before final assembly. This includes preliminary alignment, feature extraction, and position estimation that can be done quickly and efficiently, reducing the computational burden during the final image assembly stage and overall processing time.
Data Source
AI summary
A computer peripheral that may operate as a scanner. The scanner captures image frames as it is moved across an object. The image frames are formed into a composite image based on computations in two processes. In a first process, fast track processing determines a coarse position of each of the image frames based on a relative position between each successive image frame and a respective preceding image determine by matching overlapping portions of the image frames. In a second process, fine position adjustments are computed to reduce inconsistencies from determining positions of image frames based on relative positions to multiple prior image frames. When the determined position of multiple image frames overlap, pixels in the composite image may be formed by combing values of pixels in the image frames, which improves image quality of the composite image.