Long Distance Sea Surface Images Fast Sparse Matching by Integrated Feature Vector
| Autor: | Cunwei Lu, Ying Yang, Chenhao Chen |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Surface (mathematics)
Brightness Matching (graph theory) Computer science business.industry Feature vector Cosine similarity ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image (mathematics) Feature (computer vision) Computer Science::Computer Vision and Pattern Recognition Computer vision Artificial intelligence business Binocular vision |
| Zdroj: | Lecture Notes in Electrical Engineering ISBN: 9789813294400 |
| DOI: | 10.1007/978-981-32-9441-7_86 |
| Popis: | Correspondence matching is a fundamental task of stereo binocular vision system. This paper proposes a fast spares correspondence matching method used for long distance sea surface images which possesses no obvious structure and color distribution features, simultaneously, requires high processing accuracy and speed. To solve the problem of lacking obvious features, the paper extracts sea waves out from sea surface image as feature points and gathers sea waves’ size, shape, brightness, location and lengths in four orientations to realize descriptors fusing and form feature vector. To complete stereo matching fast and accurately, the paper utilize cosine similarity to match feature vectors generated in first step. The correspondence verification is carried out by the final 3D measurement result. Experiments on various real sea surface image pairs are operated to validate the effectiveness of proposed method. The comparisons between our method and some state-of-the-art methods are carried out to display the advantage of our method in precision. |
| Databáze: | OpenAIRE |
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