This paper presents a new template matching method based on marker-controlled watershed segmentation (TMCWS). It is applied to recognize numbers on special metal plates in production lines where traditional image recognition methods do not work well. TMCWS is a shape based matching method that uses different pattern images and their corresponding marker images as probes to explore a gradient space of an unknown image to determine which pattern best matches a target object in it. Different from other matching algorithms, TMCWS firstly creates a marker image for each pattern, and then takes both the pattern image and its corresponding marker image as a template window and shifts this window across a gradient space pixel by pixel to do a search. At each position, the marker image is used to try to extract the contour of the target object with the help of marker-controlled watershed segmentation, and the pattern image is employed to evaluate the extracted shape in each trial. All of the pattern images and their corresponding marker images are tried and the pattern that best matches the target object is the recognition result. TMCWS contains shape extraction procedures and it is a high-level template matching method. Experiments are performed with this method on nearly 400 images of metal plates and the test results show its effectiveness in recognizing numbers in noisy images.