Fake Hilsa Fish Detection Using Machine Vision
This addresses food safety and fraud issues for consumers and authorities in Bangladesh, though it is an incremental application of existing deep learning methods to a new domain.
The researchers tackled the problem of detecting fake Hilsa fish being sold in Bangladesh by developing a machine vision method, achieving a classification accuracy of 97.02% using DenseNet201 on a dataset of over 16,000 images.
Hilsa is the national fish of Bangladesh. Bangladesh is earning a lot of foreign currency by exporting this fish. Unfortunately, in recent days, some unscrupulous businessmen are selling fake Hilsa fishes to gain profit. The Sardines and Sardinella are the most sold in the market as Hilsa. The government agency of Bangladesh, namely Bangladesh Food Safety Authority said that these fake Hilsa fish contain high levels of cadmium and lead which are detrimental for humans. In this research, we have proposed a method that can readily identify original Hilsa fish and fake Hilsa fish. Based on the research available on online literature, we are the first to do research on identifying original Hilsa fish. We have collected more than 16,000 images of original and counterfeit Hilsa fish. To classify these images, we have used several deep learning-based models. Then, the performance has been compared between them. Among those models, DenseNet201 achieved the highest accuracy of 97.02%.