AUTOMATIC FRUIT BLEMISH DETECTION

A machine vision system for automatic detection of blemishes on fruits is presented. To increase image contrast and deal with natural variations in fruit surface colour, appropriate spectral regions are used. As blemishes usually appear as discoloured patches in fruit images, they are treated as catchment basins in grey-level landscapes. A flooding algorithm has been developed to detect the basins, i.e. the patches. Stalk and calyx areas also appear as dark patches in images when non-orientated fruits are presented, and a separation of them from blemishes is necessary. Since many defects occur on the flat or convex surfaces of a fruit while the surface around the stalk or calyx is often concave, the 3D information of surface shape is helpful in the separation. Structured light is used to obtain the qualitative information about fruit geometric shape. Incorporating the information with features extracted from grey level images, a neural network is trained to classify each detected patch as blemish or stalk/calyx. The experimental results with apples, peaches and apricots demonstrate that the system can detect blemishes on them.