Automatic classification of cotton boll using signature curve and boundary descriptors

The correlation between the environmental features and image features of cotton bolls is the necessary step for the pattern recognition and translate those features for machine understanding is the main challenge to distinguish mature cotton boll from immature one. Present work is tried to solve this problem using shape based features. The fuzzy based classifier is introduced for the decision making. Any improper acquisition of images of cotton bolls, like intense illumination or deep shadows (which is of course absent in natural settings) will produce improper results.