Indicia Location Coprocessor Using Front-End Image Statistics
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Solution Overview
Problem
Traditional indicia readers experience processing bottlenecks due to strain on the digital interconnection between the initial image processor and the host processor, particularly when handling large-sized image data or high frame rates, which slows down processing frame rates.
Innovation Solution
Implementing a front-end processing assembly that determines image statistics and indicia locations, reducing the processing load on the host processor by segmenting image data into blocks and analyzing properties like contrast and intensity, and communicating only the necessary indicia location data to the host processor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the host processor processes all image data directly, then processing completeness is maintained, but processing speed decreases due to bottleneck in digital interconnection
Solution Approach 1:
The processing architecture is segmented into three functional components: image sensor, front-end processing assembly, and host processor. The front-end processing assembly independently determines image statistics and indicia locations, dividing the processing workload and reducing the burden on the host processor's digital interconnection.
Solution Approach 2:
The front-end processing assembly extracts and pre-determines critical information (indicia locations and image statistics) before data reaches the host processor. This extraction reduces the amount of data transmitted over the digital interconnection, alleviating the bottleneck and improving processing frame rate.
2Productivity
If large sized image data is processed at high frame rates, then processing capacity increases, but digital interconnection strain increases causing bottleneck
Solution Approach 1:
The front-end processing assembly performs preliminary processing by determining image statistics and indicia locations before the data is transmitted to the host processor. This preliminary action filters and prepares only the essential information, reducing the data volume and interconnection strain while maintaining high processing capacity.
3Speed
If the host processor handles all processing tasks, then processing flexibility is maintained, but processing speed decreases
Solution Approach 1:
The front-end processing assembly acts as an intermediary between the image sensor and the host processor. It performs preliminary processing tasks (determining image statistics and indicia locations) and passes only the necessary information to the host processor, thereby increasing decoding speed while reducing the host processor's workload.
Data Source
AI summary
An indicia location coprocessor is disclosed herein. An example indicia location coprocessor includes imaging device comprising: (1) an image sensor to capture image data; (2) a front-end processing assembly configured to: (i) receive the image data and determine image statistics for the image data, (ii) determine, from the image statistics, an indicia location corresponding to a set of point coordinates in the image data, and, (iii) communicate the image data and the determined indicia location to a host processor communicatively coupled to the front-end processing assembly; and (3) wherein the host processor is configured to receive the image data and the indicia location and is configured to decode an indicia in the image data based upon determining a position in the image data corresponding to the indicia location.