Meat Adulteration Detector helps to solve the prblem of substitution of red meat. In a particular season and region sometimes one prticular red meat can be expensive. In tha case the meat vendors may substitute the required red meat with some other red meat like pork, buffalo meat, etc. This can be harmful to the consumers who are allergic to certain red meat. Using the meat adulteration detector application all that the cpnsumer will have to do is to takle a picture of the raw red meat that he/she is going to purchase and the application rightly tells whether the meat is adulterated by mixing with other red meat or not.
The application is based on the concepts of machine learning ad computer vision. The image captured by the consumer is compared with the repository of images in the dataset containing images of unadulterated red meat. The featutres of the source (dataset images) and the target (image captured by the consumer) are compared. The feature matching lines are plotted using matplotlib between sorce and target. If more than 50% of the lines are matched then we have programmed the application to display the message that the red meat is unadulterated else it labels the meat as adulterated one. Thios way the customers can ensure whether they are eating the red mest tha they asked for.