Study, Hidden Markov Model-based Object Orientation

Localization of an object in an image is always an interesting and challenging research task in the fields of image processing and computer vision. The technology of object localization has a shining perspective and plays an important role in the area of military, medicine and computer science, such as industry automation, intelligence control, computer-aided diagnose, human-machine-communication systems and precise targeting weapons.In this paper we propose a novel approach to localization of a linear structure object (spine) in medical images based on 1-dimensional Hidden Markov Model. With the analysis and understanding of the classical Viterbi algorithm and the consideration of actual condition, a specific localization algorithm derived from Viterbi algorithm is presented for determining a feature sequence in a test image, from which the position of a linear structure object could be obtained. Meanwhile, with the effective use of the heuristic information provided by the object to be located, the proposed algorithm overcomes the limitation and has a higher level of speed and veracity. To verify the validity of the novel approach, many localization experiments have been carried out with actual X-ray medical images of human spines as the experimental sets. Those results show that a linear structure object in images can be fast located by using the proposed HMM approach and the restrictions to images is little compared with the traditional methods of object localization. According to the experimental results, the effect of different parameterisations of the model on the localization performance is investigated and conclusions are drawn for establish HMM prototype better. Finally, some thoughts for improving localization performance are proposed, which is worth in promoting the approach to object localization based on HMM for practicality.