Automatic Image Segmentation Algorithm for Microscopic Images of Liquorice and Rhubarb

Abstract

This paper proposes an automated algorithm for plant identification using microscopic images of powder of herbal plants. In current scenario, the task of identifying plant from its powder form is done by pharmaceutical companies, which perform this task manually. This process takes lots of effort and time. Microscopic image of powder contains varieties of information, which are important evidence for identification of the plant. With every image, different type of noise are present, which makes the segmentation as a critical job. In this paper, we are proposing an algorithm which performs this task automatically by a computer. Our method consists two steps: "Pre-Processing" and "Image Segmentation". Firstly, microscopic images of "Liquorice" and "Rhubarb" plants were taken. On those images Top-hat and Bot-hat transformation are performed. Wiener Filter is used for image smoothing. An image segmentation is performed using Otsu's thresholding algorithm and find region of interest. The extra blobs were removed using morphological operations. Our proposed algorithm shows the efficiency for successfully detection of Liquorice and Rhubarb plants are 91.37% and 92.94% respectively.