Machine vision techniques for somatic coffee embryo morphological feature extraction

Machine vision algorithms were developed to examine somatic coffee embryo morphological features between maturation and germination stages. A skeleton morphological feature was extracted and recognition rules were established to identify “Y” shaped skeletons. An improved thinning algorithm was developed to obtain single-pixel-width skeletons that simplified the recognition task. The “Y” shaped skeleton was found to be a promising feature to represent torpedo stage embryo. For the 127 embryos tested, the success rate was 73% in identifying torpedo-stage somatic coffee embryos from the selected morphological feature.