A real-time approach for automatic food quality assessment based on shape analysis

Products sorting is a task of paramount importance for many countries' agricultural industry. An accurate quality check assures that good products are not wasted, and rotten, broken and bent food are properly discarded, which is extremely important for food production chains. Such products sorting and quality controls are often performed with consolidated instruments, since simple systems are easier to maintain, validate, and they speed up the processing in terms of production line speed and products per second. Moreover, industries often lack advanced formation, required for more sophisticated solutions. As a result, the sorting task for many food products is mainly done by color information only. Sorting machines typically detect the color response of products to specific LEDs with various light wavelengths. Unfortunately, a color check is often not enough to detect some very common defects. The shape of a product, instead, reveals many important defects and is highly reliable in detecting external objects mixed with food. Also, shape can be used to take detailed measurements of a product, such as its area, length, width, anisotropy, etc. This paper proposes a complete treatment of the problem of sorting food by its shape. It treats real-world problems such as accuracy, execution time, latency and it provides an overview of a full system used on state-of-the-art measurement machines.