A method for analyzing and searching 3D models includes steps of obtaining data global features and data local features of data images by globally analyzing and locally analyzing data images of 3D models respectively; obtaining searching global features and searching local features by globally analyzing and locally analyzing searching images respectively; obtaining corresponding data global features and corresponding data local features based on the search global features and the searching local feature; and obtaining corresponding data images based on the corresponding data global features and the corresponding data local features.

A biometrics information registration method for causing a computer to execute a process including extracting vein data representing a vein image and a feature amount from an image obtained by an image obtainment unit; and making a storage unit store the vein data and the feature amount, wherein the feature amount includes a first feature amount representing a relationship between two of a plurality of segments obtained by vectorizing the vein image.

Systems and methods for detecting and aligning land property boundaries on aerial imagery are provided. The system receives an aerial imagery having land properties. The system applies a feature encoder having a plurality of levels to the aerial imagery. A first level of the plurality of levels includes a convolution block and a discrete wavelet transform layer. The discrete wavelet transform layer decomposes an input feature tensor to the first level into a low-frequency band and a high-frequency band. The high-frequency band is cached and processed with side-convolutional blocks before the high-frequency band are passed to a feature decoder. The system applies the feature decoder to an output of the feature encoder based at least in part on one of inverse discrete wavelet transform layers. The system determines boundaries of the one or more land properties based at least in part on a boundary cross-entropy loss function.

In a method of optical proximity correction (OPC) modeling, a resist image (RI) model is generated from an aerial image (AI) of a pattern. A light intensity of a portion having a level lower than a truncation level is replaced with the truncation level in an image profile of the RI model. The image profile is smoothed to remove a sharp point in the image profile. A Laplacian kernel is applied to the image profile to generate a contour image profile. A portion of the contour image profile having a value lower than a given level is truncated. A radius of curvature kernel is applied to the contour image profile. A reciprocal number of the radius of curvature is applied to the RI model.