Particle Boundary Detection via Patch Merging
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Solution Overview
Problem
Current methods for analyzing particles in dilute fluid samples struggle to detect low contrast particles and often misclassify different parts of the same object as separate entities, leading to incorrect classification and reported element quantity.
Innovation Solution
A method and apparatus that automatically locate the boundary of an object in a field of view by forming an electronic image, identifying edge segments, forming patches around these segments, and performing a patch merge process based on proximity thresholds to accurately identify and merge overlapping patches representing a single particle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If brightness difference detection is used to identify particles, then simple implementation is achieved, but low contrast particles cannot be efficiently detected
Solution Approach 1:
The patent segments the particle detection process into multiple stages: edge detection to identify boundary pixels, patch formation to group adjacent edge pixels into rectangular regions, and patch merging to combine overlapping patches. This segmentation allows the system to detect low contrast particles by focusing on edge information rather than relying solely on brightness difference, thereby improving detection reliability while maintaining implementation simplicity.
2Measurement precision
If edge detection and patch merging are implemented, then particle identification accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary edge detection to identify all edge pixels before forming patches. This preliminary action creates a foundation that simplifies subsequent patch formation and merging operations, as the edge pixel groups provide predetermined structure that guides the patch merging process, thereby reducing overall processing complexity while maintaining high measurement precision.
Solution Approach 2:
The patent merges adjacent and overlapping patches into unified particle representations. By combining multiple edge-detected patches that overlap or are in close proximity, the system achieves accurate particle boundary location while the merging operation itself is designed to be computationally efficient, thus balancing improved measurement precision with acceptable processing complexity.
3Reliability
If different parts of the same object are identified as separate objects, then detection sensitivity is increased, but classification accuracy decreases
Solution Approach 1:
The patent merges patches that represent different parts of the same particle based on their spatial proximity and overlap. This merging operation ensures that fragmented edge detections of the same particle are combined into a single unified particle representation, thereby maintaining high detection sensitivity while improving classification accuracy by preventing misidentification of particle parts as separate objects.
Data Source
AI summary
A method and apparatus for locating the boundary of an object. An electronic image of the object is formed, having a plurality of image pixels. Groups of the image pixels are identified that represent edge segments of the object. Patches are formed around the image pixel groups, where each patch is dimensioned and positioned to entirely contain one of the image pixel groups. A patch merge process is preformed that merges any two of the patches together that overlap each other by a predetermined amount, to form a merged patch that is dimensioned and positioned to entirely contain the two merged patches. The merge process continues for any overlapping patches and merged patches until none of the patches and the merged patches overlap each other by the predetermined amount. All the edge segments contained within one of the merged patches are associated as representing the boundary of the object.