Statistical Conveyor-Belt Classification for Watermark Detection

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Solution Overview

Problem

Camera-based systems in industrial and retail environments face challenges in efficiently processing limited-time frames to detect and decode machine-readable indicia, such as digital watermarks, due to resource constraints and the need to search large composite images for indicia.

Innovation Solution

A method involving image processing to identify and prioritize specific areas within an image frame for decoding, using downsampling and object detection to reduce processing time and resources, including dividing image blocks into sub-blocks, determining average pixel values, and establishing keep-out intervals to focus decoding efforts on likely watermark locations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the entire image frame is processed for watermark detection, then detection completeness is improved, but processing time and resource use increase

Engineering Contradiction:

Improvedetection completenessVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The image frame is divided into multiple blocks, and each block is further divided into sub-blocks. This segmentation allows the system to process only relevant regions rather than the entire image, reducing processing time while maintaining detection completeness through systematic coverage of all blocks.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies different processing strategies to different regions of the image based on their likelihood of containing watermarks. Blocks with pixel values within the keep-out interval are skipped, while blocks outside this interval undergo full watermark detection, optimizing resource allocation based on local characteristics.

Inventive Principle:

Principle #3Local quality

2Reliability

If the entire image frame is processed for watermark detection, then detection completeness is improved, but resource use increases

Engineering Contradiction:

Improvedetection completenessVSAvoidcomputing resources

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent extracts and removes blocks that are unlikely to contain watermarks (those with pixel values within the keep-out interval) from the processing pipeline. This extraction principle eliminates unnecessary computation on irrelevant image regions, significantly reducing computing resource consumption while preserving detection completeness for promising blocks.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of performing full watermark detection on every block, the patent applies partial action by first filtering blocks using histogram-based pixel value analysis. Only blocks that pass this preliminary filter undergo the computationally intensive watermark detection process, optimizing resource usage.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If histogram analysis is performed on the entire image, then accuracy in identifying watermark locations is improved, but processing time increases

Engineering Contradiction:

Improvewatermark location identification accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The histogram analysis is performed on individual sub-blocks rather than the entire image. Each sub-block's pixel values are analyzed independently to determine whether the corresponding block should be processed for watermark detection, enabling precise local analysis without the computational burden of global analysis.

Inventive Principle:

Principle #1Segmentation

4Productivity

If keep-out intervals are established around histogram peak pixel values, then processing efficiency is improved, but risk of missing watermarks increases

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidwatermark detection reliability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system uses histogram analysis to establish keep-out intervals and dynamically adjusts processing decisions based on this feedback. Blocks with pixel values within keep-out intervals are skipped, while those outside undergo full detection, creating a feedback loop that optimizes the balance between processing efficiency and detection reliability based on actual image characteristics.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12423942B2Statistical classification systems and methods for distinguishing content items from conveyor belts in automated detection environments

Publication Date: 2025.09.23 DIGIMARC CORP

AI summary

The present technology relates to image signal processing. One aspect of the present technology involves analyzing reference imagery (e.g., depicting a conveyor belt) gathered by a camera system to determine which parts of an image frame offer higher probabilities of—relative to other image parts—containing content items. Image blocks representing localized content items can be provided to a signal detector to decode a signal.