Classifying image analysis techniques from their output
In this paper we discuss some main image processing techniques in order to propose a classification based upon the output these methods provide. Because despite a particular image analysis technique can be supervised or unsupervised, and can allow or not the existence of fuzzy information at some st...
| Authors: | , , , , |
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| Format: | article |
| Status: | Versión aceptada para publicación |
| Publication Date: | 2016 |
| Country: | España |
| Institution: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repository: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/132433 |
| Online Access: | http://hdl.handle.net/10261/132433 |
| Access Level: | Open access |
| Keyword: | Image segmentation Image classification Edge detection Fuzzy sets Machine learning Graphs |
| Summary: | In this paper we discuss some main image processing techniques in order to propose a classification based upon the output these methods provide. Because despite a particular image analysis technique can be supervised or unsupervised, and can allow or not the existence of fuzzy information at some stage, each technique has been usually designed to focus on a specific objective, and their outputs are in fact different according to each objective. Thus, they are in fact different methods. But due to the essential relationship between them they are quite often confused. In particular, this paper pursues a clarification of the differences between image segmentation and edge detection, among other image processing techniques. |
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