Evaluating contour segment descriptors
| Autor: | Cong Yang, Marcin Grzegorzek, Kimiaki Shirahama, Ewa źUkasik, Oliver Tiebe |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Matching (statistics) business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Boundary (topology) Pattern recognition Context (language use) 02 engineering and technology Object detection Computer Science Applications 020901 industrial engineering & automation Transformation (function) Hardware and Architecture 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Enhanced Data Rates for GSM Evolution Artificial intelligence business Scaling Rotation (mathematics) Software Mathematics |
| Zdroj: | Machine Vision and Applications. 28:373-391 |
| ISSN: | 1432-1769 0932-8092 |
| DOI: | 10.1007/s00138-017-0823-9 |
| Popis: | Contour segment (CS) is the fundamental element of partial boundaries or edges in shapes and images. So far, CS has been widely used in many applications, including object detection/matching and open curve matching. To increase the matching accuracy and efficiency, a variety of CS descriptors have been proposed. A CS descriptor is formed by a chain of boundary or edge points and is able to encode the geometric configuration of a CS. Because many different CS descriptors exist, a structured overview and quantitative evaluation are required in the context of CS matching. This paper assesses 27 CS descriptors in a structured way. Firstly, the analytical invariance properties of CS descriptors are explored with respect to scaling, rotation and transformation. Secondly, their distinctiveness is evaluated experimentally on three datasets. Lastly, their computation complexity is studied. Based on results, we find that both CS lengths and matching algorithms affect the CS matching performance while matching algorithms have higher affection. The results also reveal that, with different combinations of CS descriptors and matching algorithms, several requirements in terms of matching speed and accuracy can be fulfilled. Furthermore, a proper combination of CS descriptors can improve the matching accuracy over the individuals. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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