Basic Studies on Automatization of Chrysanthemum Cutting Sticking Operation (Part 1)

Development of Chrysanthemum Cutting Recognizing Algorithm by Use of Color Image and Chain Code

Abstract

A cutting sticking operation is laborious and requires long time especially for a large amount of chrysanthemum seedlings in Japan. In this paper, a detecting algorithm of chrysanthemum cutting is described for automation of the cutting sticking operation. An image of the chrysanthemum cutting was acquired by a color TV camera and a stem end of the cutting was detected on a thresholding image by combination to use MFN (Most Frequent Number) method based on chain code and a method to recognize the stem shape around a candidate point of the stem end. From the experimental results, it was observed that its success rate was 88% and that 1.5 seconds was required for the detection.