A two-step algorithm is presented for thinning noisy images. The first step consists of removing noisy spurs from an image using a combination of morphological operations. In the second step, thinning is performed by using the standard morphological skeleton transform (MST). This approach is useful in model-based vision applications where the features of the image are required for object recognition. The use of this algorithm in sensor array imaging situations is demonstrated.