Recognition Algorithm for Biological and Criminalistics Objects
| Autor: | Sergey D. Kulik, Alexander N. Shtanko |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Structure (mathematical logic)
Similarity (geometry) Artificial neural network Computer science business.industry Pattern recognition 02 engineering and technology Automation Task (project management) Impression 03 medical and health sciences 0302 clinical medicine Pattern recognition (psychology) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Element (category theory) business 030217 neurology & neurosurgery |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030257187 BICA |
| DOI: | 10.1007/978-3-030-25719-4_36 |
| Popis: | This paper describes the results of a work to develop an algorithm for analyzing images of embossed impressions in paper documents under oblique lighting. The described algorithm could also be used for recognition of similarly-structured objects, for example, some of biological structures. This type of analysis is necessary during forensic analysis of certain security features of paper documents. Part of this analysis is determining to which category new, uncategorized impression belongs to. This research explores the potential for automation of this task using neural networks. The core element of the algorithm is a neural network which determines the similarity between two embossed impressions. The paper describes the structure of the algorithm, a method for creating an image database for training and testing, as well as testing results for proposed algorithm. |
| Databáze: | OpenAIRE |
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