Authors:
Igor G. Olaizola
1
;
Iñigo Barandiaran
1
;
Basilio Sierra
2
and
Manuel Graña
2
Affiliations:
1
Vicomtech-IK4 Research Alliance, Spain
;
2
UPV-EHU, Spain
Keyword(s):
Feature Descriptor, Trace Transform, Image Matching, Image Characterization.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
Abstract:
Global and local image feature extraction is one of the most common tasks in computer vision since they
provide the basic information for further processes, and can be employed on several applications such as
image search & retrieval, object recognition, 3D reconstruction, augmented reality, etc. The main parameters
to evaluate a feature extraction algorithm are its discriminant capability, robustness and invariance behavior to
certain transformations. However, other aspects such as computational performance or provided feature length
can be crucial for domain specific applications with specific constraints (real-time, massive datasets, etc.). In
this paper, we analyze the main characteristics of the DITEC method used both as global and local descriptor
method. Our results show that DITEC can be effectively applied in both contexts.