Background Starches will be the primary storage space polysaccharides in vegetation and so are distributed widely throughout vegetation including seeds, origins, tubers, leaves, stems and so on. the oversegments to the objects with comparable features. Experimental results demonstrate that this proposed method can alleviate oversegmentation of watershed segmentation algorithm successfully. Conclusions We present a new scheme for starch granules segmentation. The proposed scheme aims to alleviate the oversegmentation in watershed algorithm. We use the shape information and critical points of gradient vector flow (GVF) of starch granules to identify oversegments, and use fuzzy c-mean clustering based on prior knowledge to merge these oversegments to the objects. Experimental results on twenty microscopic starch images demonstrate the effectiveness of the proposed scheme. Background Starch, the complex carbohydrate, is a major component in human diet. It has also been widely used in industrial applications such as making food, health and nutrition, pharmaceutical and personal care. The natural starch is produced in chloroplasts by photosynthesis and it is usually packed into granules with a layered structure [1][2]. The shape and size of native starch granules vary among species. For example, potato starches have large round granules and their diameters are up to 100m. Rice starch granules are the smallest of the cereal starches 940289-57-6 and are about 2m in diameters [3]. In wheat, the situation is usually more complicated. Three types of granule size distributions were reported [4]. The shape and size of starch granules can affect the starch properties and functions; starch granules for industrial application have got particular necessity within their size and shape generally. For example, starch granules for the paper commercial must have spherical form and an average even granule size. Organic starches don’t have such even characteristics, they are would have to be modified for industrial applications therefore. In the various other hands, cultivation of an assortment with particular size and shape of starch granules can be an substitute way to meet up this demand. Therefore, the brand new cultivar must be exploited and investigated. Developing a brand-new cultivar with a certain desired size of starch granules for industrial has economical significance in the agriculture science. 940289-57-6 Among CCR1 several methods to measure 940289-57-6 the shape and size 940289-57-6 of granules, microscopic evaluation is the most convenient and relatively precise way [5]. The granule images were taken from a light microscope. The shape and size can be examined directly from the image prints. The microscopy images can be converted or directly acquired into digital data and analysis automatically. In addition, with this method, starch granules can be analyzed that is that starch granules do not need to be extracted from herb tissues. data are significant for the scholarly research of starch granule advancement in linked to other cellular element. Microscopy picture analysis is a member of family basic for quick examining the starch adjustments in plant tissues for breeders who want in developing 940289-57-6 brand-new cultivars. The info from picture evaluation will be the most repeatable and specific weighed against others strategies [5], but this technique could possibly be retarded with the picture quality in more technical situations of overlapping granules. Distinguishing starch granules from history noise and determining overlapping granules certainly are a appealing way of quantitative analysis. To be able to quantitatively analyze starch granules, picture segmentation technique is adopted to portion the starch granules from the backdrop often. Segmentation is usually a challenging task due to.