Abstract
This paper presents a robust system for automatic car make recognition in real-traffic images of car front, featuring low contrast and compression-based distortions. The system is designed to distinguish and classify a variety of car makes by means of Scale Invariant Feature Transform pattern recognition and matching over a reference database of car brand images. The system framework consists of image preprocessing techniques yielding a car brand region, feature extraction and description, pattern matching procedure and multicriteria decision-making process. The knowledge database is opened and easy to extend in order to cover an increasing number of car makes. Described approach stands for a part of an expert system for car type, make and color recognition, to be designed and build for real traffic supervision.
| Original language | English |
|---|---|
| Pages (from-to) | 235-246 |
| Number of pages | 12 |
| Journal | Advances in Intelligent Systems and Computing |
| Volume | 283 |
| DOIs | |
| Publication status | Published - 2015 |
Keywords
- Car make recognition
- Feature extraction
- Scale Invariant Feature Transform
ASJC Scopus subject areas
- Control and Systems Engineering
- General Computer Science
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