2 results about "Level set segmentation" patented technology

This invention proposes a rock thin section image segmentation method based on foreground / background divide-and-conquer and layered color processing. The method first performs color space transformation and principal component analysis (PCA) dimensionality reduction on the rock thin section image to construct a single-channel structural representation for segmentation. Then, a first global segmentation is performed based on a level set model to achieve preliminary extraction of macroscopic mineral structures. Subsequently, based on the initial segmentation results, the image is divided into foreground and background regions, and enhancement channels are selected in different color spaces for each region to perform a second-stage level set segmentation. Specifically, the background region recovers weak contrast structural information by enhancing chromaticity differences, while the foreground region improves the separation ability of fine grains by enhancing texture contrast. Finally, the two segmentation results are fused, and combined with region filtering and morphological optimization, the final rock thin section segmentation result is obtained. This method can effectively improve the accuracy and stability of rock thin section image segmentation under complex lithological conditions.

The application discloses a kind of three-dimensional reconstruction method and system based on two-dimensional forward-looking sonar image, the method includes: step one: for the two-dimensional forward-looking sonar sequence collected, introduce based on mahalanobis distance detection method, determine the initial profile of local binary fitting level set segmentation method, further, using a local binary fitting (LBF) level set segmentation method, determine the target to be reconstructed region based on the initial profile detected;Step two: using the registration method based on phase correlation, the target region determined in step one is registered, and the relative displacement of sonar movement is calculated.Step three: based on the results of the above steps, using blind deconvolution algorithm, reconstructs the three-dimensional point cloud image of target.Compared with the prior art, the three-dimensional reconstruction of the target can be performed without pre-acquiring the horizontal position information of the sonar, and has certain anti-noise ability.The method disclosed in the application is more suitable for three-dimensional reconstruction of underwater targets.