Automatické třídění fotografií podle obsahu
| Autor: | Veľas, Martin |
|---|---|
| Jazyk: | čeština |
| Rok vydání: | 2013 |
| Předmět: |
SURF
k-dimensional tree color correlograms knihovna OpenCV tagování SIFT experiments experimenty image segmentation clustering dividing of image visual codebook interesting points klasifikátor segmentace obrazu soft assignment vizuální slovník měkké přirazení visual word lokální příznaky bag of words význačné body photo categorization tagging barevné příznaky color features local features shlukování kategorizace fotografii k-means barevné korelogramy classifier k-dimenzionální strom dělení obrazu OpenCV library support vector machines vizuální slovy |
| Druh dokumentu: | masterThesis |
| Popis: | This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with explicit data embeding is used for its efficiency. Finally, results of experiments with above mentioned techniques of the image categorization are discussed. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
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