63 results about "Otsu's method" patented technology

The invention discloses a method for automatically segmenting human lateral geniculate nucleus (LGN) by using prior knowledge. The method comprises the steps: firstly, carrying out bias field correction on data of a structure image of a human brain, and then, carrying out brain substructure segmentation on the corrected image, so as to obtain a template of a LGN; then, registering the corrected structure image data and the template of the LGN to a MNI (Montreal Neurological Institute) standard space; acquiring the region boundary of the LGN in the MNI space according to prior knowledge of an LGN anatomical structure, and then, segmenting the LGN in the region respectively by a region-growing method, a k-means method, an Otsu algorithm and an image segmentation method; then, fusing the segmented results, so as to obtain an estimated value of the LGN region, which serves as a segmented result; finally, transforming the segmented result into an original space of the structure image, thereby obtaining a final LGN segmented result.

A method is described to obtain a binary image from the print-and-scan process to best match the known original. A point-spread function (PSF) of the PAS process is first obtained from its knife-edge responses, and deblurring is carried out on the scanned images using deconvolution. After image deskewing and preliminary registration, a supervised adaptive thresholding procedure is utilized to binarize the scanned image such that a measure of difference (e.g. the Euclidean distance) between the original and binarized images is minimized. The supervised adaptive thresholding procedure divides the scanned images into many rectangular sub-images. Otsu's method is used to find a starting threshold for each scanned sub-image. An optimal threshold is found around the Otsu's threshold via iterative search to minimize the measure of difference between the original sub-image and scanned sub-image. The sub-images are binarized using the optimal threshold. This method may be used in document authentication.

The invention discloses a rural resident point information extraction method based on a high-resolution remote-sensing image. The rural resident point information extraction method comprises the following steps: firstly, carrying out Canny edge detection on the high-resolution remote-sensing image, and obtaining a vector edge line through chain code tracking; then, carrying out Douglas-Peucker abbreviation on a vector edge to extract straight-line segments, and rejecting shorter straight-line segments and keeping longer straight-line segments according to length constraints; secondly, according to adjacency relation between the straight-line segments and included angle constraints, extracting straight angle points, calculating the density characteristics of the straight angle points within a certain space region range, and generating a straight angle point density characteristic image, wherein the characteristic image and the input high-resolution remote-sensing image have same spatial range and spatial resolution; and finally, carrying out binarization processing on the density characteristic image by utilizing Otsu, extracting rural resident point vector pattern spots through connected component analysis so as to extract rural resident point information. Precision and effects are improved, and robustness and universality are better.