A circle detection technique and its application in counting the number of pieces of canes in a bundle are described. Pre-processing is performed on the "raw" image from the camera, to obtain a binary image that is suitable for counting. Blobs in this image are then isolated in turn and each one is analysed to extract properties of interest, including left, right, top and bottom limits of the blobs, their centroid positions, sizes, and perimeters. These measurements are further analysed, so that objects that are approximately circular can be identified. In practice, factors such as lighting, the grade of cane and physical state of the cut ends may result in degraded circular objects being present in this binary image. Possible processes for identifying “circular” objects from a fragmented image are reviewed and a novel technique is proposed.