A GRADIENT-REGION CONSTRAINED LEVEL SET METHOD FOR AUTONOMOUS ROCK DETECTION FROM MARS ROVER IMAGE
Keywords: Autonomous rock detection and analysis, Image segmentation, Mars rover image, Level set function evolution
Abstract. Rocks are one of the major Martian surface features and yield significant information about the relevant geology process and the life exploration. However, autonomous Martian rock detection is still a challenging task due to the appearance similar to the background, the view and illumination change. Therefore, this paper presents a gradient-region constrained level set method based on mars rover image for automatic Martian rock extraction. In our method, the evolution function of level set consists of the internal energy term for guaranteeing the deviation of the level set function from a signed distance function and the external energy term, where the gradient-based information is integrated with the locally adaptive region-based information, for robustly driving the motion of the zero-level set toward the object boundaries even in images with ununiform grey scale. The resulting evolution of the level set function is based on the minimisation of the overall energy functional using the standard gradient descent method. As a result, those detected Martian surface regions that are most likely to yield valuable scientific discoveries will be further analysed based on two-dimensional shape characterisation. To evaluate the performance of the proposed method, experiments were performed on mars rover image under various terrain and illumination conditions. Results demonstrate that the proposed method is robust and efficient for automatically detecting both small-scale and large-scale rocks on Martian surfaces.