Global Journal of Computer Sciences: Theory and Research

Global Journal of Computer Sciences: Theory and Research

Using local binary patterns for object detection in images

Yazarlar: Karel Petranek, Pavel Janecka, Jan Vanek

Cilt 5 , Sayı 1 , 2015 , Sayfalar -

Konular:-

Anahtar Kelimeler:Computer vision,Object detection,Local binary patterns.

Özet: The article discusses a texture operator called Local Binary Patterns (LBP) and its applications in image processing and object detection. We provide a description of the algorithm for computing LBP together with a rationale for using LBP as a feature for object detection and image recognition. Based on the algorithm we show that LBP features have a low computational overhead compared to more complicated image features such as the commonly used SIFT or SURF features or neural network based approaches because they exploit the use of extremely fast bitwise and integer operations of the CPU. We demonstrate that LBP is robust to changes in brightness, contrast, image rotation, image scale. We develop two enhancements for LBP that improve its resistance to camera noise and enhance the discriminative power of LBP when it is used as a feature for machine learning algorithms. We present the results on a challenging real-world object detection task.


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BibTex
KOPYALA
@article{2015, title={Using local binary patterns for object detection in images}, volume={5}, number={0}, publisher={Global Journal of Computer Sciences: Theory and Research}, author={Karel Petranek, Pavel Janecka, Jan Vanek}, year={2015} }
APA
KOPYALA
Karel Petranek, Pavel Janecka, Jan Vanek. (2015). Using local binary patterns for object detection in images (Vol. 5). Vol. 5. Global Journal of Computer Sciences: Theory and Research.
MLA
KOPYALA
Karel Petranek, Pavel Janecka, Jan Vanek. Using Local Binary Patterns for Object Detection in Images. no. 0, Global Journal of Computer Sciences: Theory and Research, 2015.