Content Based Image Retrieval using Histogram and LBP
DOI:
https://doi.org/10.18486/ijcsnt/5.1.063Keywords:
CBIR, Feature Extraction, Similarities Measure, Feature Vector, LBPAbstract
Image retrieval (IR) is a process of browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval is TBIR (Text Based Image Retrieval) which utilize some method of adding metadata such as captioning, keywords, or descriptions to the images so that retrieval can be performed over the annotation words. Manual image annotation is time-consuming, laborious and expensive; to address this, there has been a large amount of research done on automatic image annotation like CBIR. To improve existing CBIR performance, it is very important to find effective and efficient feature extraction mechanisms. This research aims to improve the performance of CBIR using Color and Texture features.
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