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Quaternion based segmentation for vanilla recognition

Vanilla is the second most expensive spice worldwide. The high cost of vanilla has led to the problem of dangerous adulterated substitutes. Its high cost is attributed largely to the labor intensive hand pollination required where the melipona bee is not present. This article proposes a method of segmenting vanilla images intended for robotic control of a future automated pollination system. We present the specialization of a hypercomplex numbers based segmentation technique for vanilla flower recognition. The specialization overcomes much of the difficulty of differentiating green flowers from their similarly colored surroundings. Comparison is given to previous hypercomplex numbers based segmentation without the specialization.