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Detection and Classification of Gram-negative Bacteria in Water Samples Using Viola-Jones Algorithm

Enterobacteriaceae is a family of gram-negative bacteria which can be found in water samples. Some of its strains causes diseases to human body. In this study, the researcher employed the Viola-Jones algorithm to detect the shape and classify Enterobacteriaceae in a sample. A Raspberry Pi camera attached to a compound microscope was used to capture the image; the software utilized was Python, a powerful programming language optimized for programmers for high quality use. Confusion matrix was used to check the accuracy of the data obtained from the proposed system with the actual system (laboratory). Under random sampling, three trials were made in 10 samples. The results showed an accuracy of 84.44% for detecting the shape of the bacteria, and 84.44% accuracy in classifying the family. Therefore, the proposed system can detect the shape of bacteria and classify its family using Viola-Jones Algorithm.