A new separation algorithm based on contour segments and ellipse fitting is proposed to separate the ellipse-like touching grain kernels in digital images. The image is filtered and converted into a binary image first. Then the contour of touching grain kernels is extracted and divided into contour segments (CS) with the concave points on it. The next step is to merge the contour segments

which is the main contribution of this work. The distance measurement (DM) and deviation error measurement (DEM) are proposed to test whether the contour segments pertain to the same kernel or not. If they pass the measurement and judgment

they are merged as a new segment. Finally with these newly merged contour segments

the ellipses are fitted as the representative ellipses for touching kernels. To verify the proposed algorithm

six different kinds of Korean grains were tested. Experimental results showed that the proposed method is efficient and accurate for the separation of the touching grain kernels.