Study on detecting methods for apple stem and defected surface with computer vision - ZHANG Wen-ying; YING Yi-bin (浙江大学学报. 农业与生命科学版)
The characteristics of apple stem were studied, the existence of apple stem was detected by scanning. The different reflectance properties of defected surface and non-defected surface of apples were analyzed, the statistical properties of gray value of different pixel were analyzed too. To 15 apple pictures without stem, the classification accuracy is 100%, to 90 pictures whose stems are in good condition the accuracy is 88%. This classification lasted about 1 second, the R (Red) value was used to find the suspected defected pixel, the defected area was found by region growing method and the non-defected pixel (including the stem and the calyx) was discarded. Finally, the total defected area of the whole apple was worked out. The tests proved that the method for detecting defected surface was efficient.