Off-the-shelf hardware used for detection, identification and quantification of potato defects

A prototype computer vision system has been used to identify substandard potatoes. The machine vision system used off-the-shelf hardware to enable affordable detection, identification and quantification of common defects affecting potatoes.

The main factor affecting consumer preference is physical appearance, with clear unblemished skin a significant selling point. Potatoes with defects, diseases and blemishes are generally avoided. Most potatoes are sorted into different grades by hand, often resulting in mistakes and losses.

The University of Lincoln team from the Centre for Vision and Robotics Research worked with the Potato Council to produce a low-cost system which can assist quality control staff and improve consistency, speed and accuracy of defect identification and quantification.

Director of the Centre for Vision and Robotics Research, Dr Tom Duckett, said: “The system relies on initial input by an expert, identifying blemishes, diseases, as well as good specimens, from sample batches of potatoes. The graphical user interface was developed to allow the software to be used by quality control experts from the industry. The system can be trained to recognise different defect types and will analyse potatoes in near-real-time - a significant improvement on previous research in this area.”

The system developed uses off-the-shelf hardware, including a low-cost vision sensor and a standard desktop computer with a graphics processing unit, together with software algorithms to enable detection, identification and quantification of common defects affecting potatoes. The system uses state-of-the-art image processing and machine learning techniques to automatically learn the appearance of different defect types. It also incorporates an intuitive graphical user interface to enable easy set-up of the system by quality control staff working in the industry.

Postgraduate students from the Centre for Vision and Robotics Research played a major role in the project with Michael Barnes (PhD student) undertaking underpinning theoretic research, while Jamie Hutton (MSc student) was responsible for researching and developing the real-time prototype for industry testing. The team worked with Glyn Harper from Sutton Bridge Crop Storage Research - the leading post-harvest applied research facility for agricultural storage in the UK. It is owned by the Agriculture & Horticulture Development Board and operated by its Potato Council division.

The British potato industry is worth around £3.5 billion a year and potatoes account for 40% of the carbohydrate consumed in the UK.

University of Lincoln
www.lincoln.ac.uk