Identification of Salt Applying Image Processing and Machine Learning Techniques

Salt is essential today due to its numerous applications in food, healthcare, and other industries. Several varieties of salt are available on the market, and each has distinct physical features that are recognized based on its size, shape, color, and texture. Despite these claims, a system that could distinguish salt is still non-existent. Furthermore, carrying out this study could provide solution to the salt industry's need for more technology and innovation. In addition, using image processing and machine learning techniques, this study created a system to identify five distinct types of salt: Pink Himalayan, Black Himalayan, Black Lava, Kosher, and Sea salts. The researchers utilized different image processing algorithms such as the K-means, CLAHE, Grayscale, Gaussian Blur, Dilation, Morphology, and Erosion to enhance salt images. The Canny Edge Detection (CED) was utilized for feature extraction, while the SVM was used to identify five distinct kinds of salt. The system developed is implemented using a Raspberry Pi 4 microcontroller for hardware development. The researchers also used a microscopic camera to capture salt samples. Overall, the researchers obtained an accuracy of 96.218% while implementing the algorithm.