Automatic Segmentation of Touching Rice Grains Using Image Processing

In the process of intellectualized visional testing products, valid image information is often collected to analysis for objective parameters such as quantity, size, and shape and so on. Because there is phenomenon of touch, the objects needs to be segmented accurately. This paper presents a novel image processing algorithm that has been developed and tested for the accurate segmentation of touching rice grains in digital images. This algorithm uses general shape properties for initial decision making, then use Erosion and dilation technique for segmented the touching grains at the point of contact. This approach offers a cautious, decisive and reliable segmentation between small sets of touching rice grains. The result of the experiments shows that touching objects can be segmented with the accuracy near 100% with this method, that the shape of the object is not to be changed, which can meet the demand of analysis of object characteristics in intellectualized visional testing process, and that it has a practical value.