Optical Code Scanner Multi-Resolution Processing

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Solution Overview

Problem

Optical code scanners face challenges with non-uniform illumination and geometrical distortion when reading two-dimensional codes, which complicates contrast variations and processing efficiency, especially without specialized hardware acceleration devices.

Innovation Solution

The method involves capturing high-resolution images and generating a sequence of reduced resolution images, enhancing contrast on the lowest resolution image, identifying regions of interest, correcting geometrical distortion, and recovering optical code data using standard processing power without additional hardware.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If hardware acceleration devices are used to process captured images, then processing speed meets requirements, but device cost increases and availability decreases

Engineering Contradiction:

Improveprocessing speedVSAvoidhardware requirements

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces specialized hardware acceleration devices with software-based image processing algorithms that run on standard processors. The method uses multi-resolution analysis and selective region processing to achieve fast code detection without requiring dedicated hardware, thus substituting mechanical/hardware solutions with software-based alternatives.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent divides the full-resolution image into multiple resolution levels and identifies regions of interest at lower resolutions before processing those specific regions at full resolution. This segmentation approach reduces the total processing load on standard hardware, enabling fast performance without specialized acceleration devices.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If full-resolution images are processed for code detection, then detection accuracy is maintained, but processing time increases

Engineering Contradiction:

Improvecode detection accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the image processing task by first analyzing down-sampled versions to identify potential code regions, then applying full-resolution processing only to those specific regions. This maintains detection accuracy while significantly reducing overall processing time compared to analyzing the entire full-resolution image.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies full processing power selectively only to regions that contain potential codes, rather than processing the entire image at full resolution. This partial action approach maintains accuracy for code detection while avoiding unnecessary processing time spent on regions without codes.

Inventive Principle:

Principle #16Partial or excessive action

3Reliability

If image enhancement functions are applied to the entire captured image, then image quality improves, but processing load increases

Engineering Contradiction:

Improveimage qualityVSAvoidprocessing load

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent applies image enhancement functions such as contrast adjustment and distortion correction only to identified regions of interest rather than the entire captured image. This local quality approach maintains reliable image quality in code regions while significantly reducing the processing load and energy consumption.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS9147095B2Optical code scanner optimized for reading 2D optical codes

Publication Date: 2015.09.29 NCR VOYIX CORP

AI summary

An optical code scanner is presented that includes image capture technology to read optical codes. The optical code scanner captures an image of an optical code and then generates multiple reduced resolution versions of the image. Multiple techniques are applied to the different images to identify a region of interest, enhance the contrast of the image, perform a non-linear local geometrical distortion correction and minimize the spatial resolution required to read the optical code. The techniques reduce the raw processing power and time required to identify and read an optical code.