Apple watercore sorting system using X-ray imagery: I. Algorithm development

Watercore is an internal disorder that leads to breakdown of tissue and pos sibly loss or downgrade of the product. It is very difficult to determine w hether an apple contains watercore or not, especially in the early stages, based solely on external information, since watercore does not alter extern al texture until after severe internal breakdown. In this study, we explore d the possibility of using two-dimensional (2-D) X-ray imaging to detect in ternal watercore damage in apples. The algorithm to detect Red 'Delicious' watercore apples consists of two stages, the first stage extracts features from the apple x-ray. image and the second stage categorizes apples into di fferent watercore levels using the features identified. A total of eight fe atures were extracted from an x-ray scanned apple image and these features were fed into neural network classifier to categorize them into three diffe rent classes, clean, mild, and severe. The results showed that the system w as able to correctly recognize apples into clean and severe categories with in 5-8% false positive and negative ratios. The result also showed that the algorithm was able to recognize apples independent of apple orientation, b ut only if the stem-calyx axis made a fixed angle with the x-ray beam. Sort ing at random apple orientation was not tested. The estimated speed of the system, if implemented on a DSP board, will be fast enough to keep up with the current apple processing line.