Detection and Recognition of Moving Objects using the Moving Mask Method and the Hidden Markov Model

This paper proposes a new detection and recognition method for moving objects that uses the moving mask method and the hidden Markov model. First, we apply the concept of entropy to convert the pixel value in the image domain into the amount of energy change in the entropy domain. Second, we find the coarse region of moving objects by automatically generating the moving mask image from the inter-frame difference between two transformed entropy images. Third, we use the discrete wavelet transformation technique to extract proper feature vectors from the detected mask image. Fourth, we use the hidden Markov model to accurately recognize moving objects. The results indicate that our proposed method can effectively and accurately detect and recognize moving objects in image sequences.