Abstract—Color detection [1] is the process of detecting name of the color. Here this is easy task for humans to detect the color and choose one. But computer cannot detect the color easily. This is tough task for computer to detect the color easily. So that’s why we choose this project. Many of the project and research papers are written on this problem. But we use different techniques for this project. Naive Bayes algorithm, Pandas and OpenCV libraries used in python languages. Naive Bayes may be a simple technique for constructing classifiers: models that assign class labels to problem instances, represented as vectors of feature values, where the category labels are drawn from some finite set. There’s not one algorithm for training such classifiers, but a family of algorithms supported a standard principle: all naive Bayes classifiers assume that the worth of a specific feature is independent of the worth of the other feature, given the category variable. Open Source Computer Vision Library. OpenCV was designed for computational efficiency [2] and with a robust specialize in real-time applications. Dedicated video encoding within the cloud. Panda may be a cloud-based platform that gives video and audio encoding infrastructure.

Keywords—color detection, naïve Bayes, pandas, OpenCV, python libraries

PDF | DOI: 10.17148/IJARCCE.2021.10479

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