A global and local binary pattern image crack segmentation method based on robot vision comprises the following steps: enhancing a contrast of an acquired original image to obtain an enhanced map; using an improved local binary pattern detection algorithm to process the enhanced map and construct a saliency map; using the enhanced map and the saliency map to segment cracks and obtaining a global and local binary pattern automatic crack segmentation method; and evaluating performance of the obtained global and local binary pattern automatic crack segmentation method. The present application uses logarithmic transformation to enhance the contrast of a crack image, so that information of dark parts of the cracks is richer. Texture features of a rotation invariant local binary pattern are improved. Global information of four directions is integrated, and the law of universal gravitation and gray and roundness features are introduced to correct crack segmentation results, thereby improving segmentation accuracy. Crack regions can be segmented in the background of uneven illumination and complex textures. The method has good robustness and meets requirements of online detection.

A computation unit calculates luminance differences of individual pixel pairs in a feature area and calculates, based thereon, a local feature value formed from bit values respectively corresponding to the pixel pairs. Specifically, the computation unit calculates a specific luminance difference for a specific pixel pair corresponding to a specific bit value and then compares the result with a specified range including a zero point of luminance difference. Then a first value is assigned to the specific bit value when the specific luminance difference is greater than the upper bound of the specified range. A second value is assigned to the same when the specific luminance difference is smaller than the lower bound of the specified range. A predetermined one of the first and second values is assigned to the same when the specific luminance difference falls in the specified range.

Disclosed is a computer-implemented method for determining a position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a corresponding computer program, a non-transitory program storage medium storing such a program and a computer for executing the program, as well as a system for the position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a system comprising an electronic data storage device and the aforementioned computer.

A computer implemented method for object detection includes the following steps carried out by computer hardware components: acquiring an image; determining a pixel of the image as a base pixel; determining coordinates of a plurality of sets of target pixels, each set of target pixels including a plurality of pixels in a respective pre-determined relationship to the base pixel; for each of the sets of target pixels, determining information representing values of the pixels in the respective set of target pixels; and determining whether a pre-determined object is shown in the image based on the determined information.

This disclosure is related to an image generation method and apparatus. The method includes: obtaining a first body image including a target body and a first clothes image including target clothes; transforming the first clothes image based on a posture of the target body in the first body image to obtain a second clothes image, the second clothes image including the target clothes, and a posture of the target clothes matching the posture of the target body; performing feature extraction on the second clothes image, an image of a bare area in the first body image, and the first body image to obtain a clothes feature, a skin feature, and a body feature respectively; and generating a second body image based on the clothes feature, the skin feature, and the body feature, the target body in the second body image wearing the target clothes.

Disclosed in the present invention is An annotation method of arbitrary-oriented rectangular bounding box, wherein: the elements for annotation being: the coordinates of the center point C, a vector {right arrow over (CD)} formed by the center point C and a chosen vertex D, and the ratio of the vector {right arrow over (CP)} to vector {right arrow over (CD)}, where {right arrow over (CP)} is the projection of the vector {right arrow over (CE)} to {right arrow over (CD)}, and {right arrow over (CE)} is a vector formed by the center of the bounding box to one of the vertex E that close neighbor to vertex D; and it is also required that the vector {right arrow over (CP)} is in the same direction as the vector {right arrow over (CD)}, the vertex E in either of the clockwise or counterclockwise direction of the vertex D. The symbol notation of this method is (x.sub.c, y.sub.c, u, v, ρ), x.sub.c and y.sub.c are the two coordinate values of the center point C, u and v are the two components of vector {right arrow over (CD)}, ρ is the ratio of the vector {right arrow over (CP)} to vector {right arrow over (CD)}. Also let a binary value s to indicate whether the two components of the vector {right arrow over (CD)} have same sign or not to represent {right arrow over (CD)} and −{right arrow over (CD)} at once by (|u|, |v|, s), then getting a method for annotating arbitrary-oriented rectangular bounding box that one bounding box has only two representation vectors. Its symbol notation is (x.sub.c, y.sub.c, |u|, |v|, s, ρ), wherein |u| and |v| are magnitude of two components of the vector {right arrow over (CD)}. This method avoids loss inconsistency between representations of the same bounding box and is beneficial to model regression training.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

A method for determining authenticity of a document is provided that includes receiving, by an electronic device, an image of a document, assigning a label to the image, and obtaining vectors for each image in a subset of images. Each image is of a document and is assigned the same label as the received image. Moreover, the method includes encoding the received image into a vector, calculating a distance between the vector of the received image and each obtained vector, comparing each of the calculated distances against a threshold distance, and calculating a number of the calculated distances that are less than or equal to the threshold distance. In response to determining the calculated number is at least equal to a required number, the document in the received image is determined to be authentic. Otherwise, the received image requires manual review.

The present invention belongs to the technical field of petroleum exploitation engineering, and discloses a 3D modeling method for cementing hydrate sediment based on a CT image. Indoor remolding rock cores or in situ site rock cores without hydrate can be scanned by CT; a sediment matrix image stack and a pore image stack are obtained by gray threshold segmentation; then, a series of cementing hydrate image stacks with different saturations are constructed through image morphological processing of the sediment matrix image stack such as dilation, erosion and image subtraction operation; and a series of digital rock core image stacks of the cementing hydrate sediment with different saturations are formed through image subtraction operation and splicing operation to provide a relatively real 3D model for the numerical simulation work of the basic physical properties of a reservoir of natural gas hydrate.

A method is provided for generating and revising map geometry based on a received image and probe data. A method may include: receiving probe data from a first period of time, where the probe data from a first period of time is from a plurality of probes within a predefined geographic region; generating a first image of the predefined geographic region based on the probe data from the first period of time; receiving probe data from a second period of time different from the first period of time, where the probe data from the second period of time is from a plurality of probes within the predefined geographic region; generating a second image based on the probe data from the second period of time; comparing the first image to the second image; and generating a revised route geometry based on changes detected between the first image and the second image.