In this paper, a method of edge detection from low contrast and noisy images which contain hexagonal shape is proposed. This method is based on the combination of laplacian gaussian filter and an idea of filters which are dependent on the shape. First, an algorithm which has six masks as its extractors to detect the hexagonal edges especially in the comers is used. Here, two tricom filters are used to detect the tricom joints of hexagons and other four masks are used to enhance the line segments of hexagonal edges. As a natural image, a corneal endothelial cell image which usually has a regular hexagonal shape is selected. The edge detection of hexagonal shapes in this corneal endothelial cell is important for clinical diagnosis. Next, The proposal algorithm and other conventional methods are applied to noisy hexagonal images to evaluate each efficiency. As a result, this proposal algorithm shows a robustness against noises and better detection ability in the aspects of the signal to noise ratio, the edge coineidence ratio and the detection accuracy factor as compared with other conventional methods.