Image segmentation algorithm for Phalaenopsis amabilis based on watershed algorithm and gradient

It is an important method to improve the planting profit of Phalaenopsis ababilis by the control of its anthesis through image identification technology to acquire the growing parameters of greenhouse Phalaenopsis ababilis. How to segment and extract the image of Phalaenopsis amabilis from the background image is the key point of image identification. This paper firstly uses color gradient algorithm to extract the Phalaenopsis amabilis natural images gradient image. It adopts the threshold value to find out the significant part of gradient image (e.g. the significant edge in the image), and the watershed segmentation method to segment the source image. It uses the significant edge image to determine the watershed segmentation image so as to remove the insignificant "dam" and make its both sides converge, to restrain over-segmentation effect. Finally, the target image of Phaleaenopsis amabilis will be obtained through merging the similar areas according to area merging standards. By comparing the segmentation effect with artificial method of the 20 Phalaenopsis ababilis images, it proves that the segmentation algorithm based on gradient and watershed method has good effect to extract the Phalaenopsis amabilis image from its natural background and the segmentation rate is up to 93.6%.