Efficient Retrieval of Images with Irregular Patterns Using Morphological Image Analysis: Applications to Industrial and Healthcare Datasets
Jiajun Zhang, Georgina Cosma, Sarah Bugby, Jason Watkins, Cosimo Distante · 2023
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Description
Jiajun Zhang and co-authors build a search tool that finds images with like irregular patterns. Factories and hospitals both need to pull past images that match a new one: a past fault on a line, or a past case of disease. Their 2023 paper draws a set of shape traits, called DefChars, from the odd patterns in each image rather than from color or texture alone. The traits come from morphological analysis, a way of probing shapes with simple probes.
Search then ranks stored images by how close their pattern traits sit to the query image. The team tests the framework on industrial and health data sets. Fast, pattern-based search can flag repeat faults and like cases early. The authors present shape traits as a sturdy signal where patterns are messy and uneven.
Catalog record
| CREATOR | Jiajun Zhang, Georgina Cosma, Sarah Bugby, Jason Watkins, Cosimo Distante |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 116 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |