An image processing apparatus, a method, and a program for allowing cells to be quantitatively observed. A computer obtains a cell membrane image obtained by performing fluorescent observation on a cell membrane of a cell serving as a sample and a tricellular tight junction (tTJ) image obtained by performing fluorescent observation on a protein localized in a tTJ of the cell. The computer derives the size of area of a region of the cell by identifying the region of each cell from the cell membrane image, derives the size of area of the region of the protein localized in the cell from the tTJ image, and dividing the obtained size of area of the region of the protein by the size of area of the region of the cell, thus calculating an index of adhesion strength of the cells. The invention can be applied to an observation system.

The present invention provides a method and a device for detecting interest points in an image. The method includes: acquiring an original input image; performing down-sampling processing on the original input image, so as to obtain a plurality of sampling images with different resolutions; dividing each sampling image into a plurality of small image blocks; performing filtering processing on the plurality of small image blocks in each sampling image in sequence by using Laplacian-of-Gaussian filters, so as to obtain filtered images of the plurality of small image blocks in each sampling image; and acquiring interest points in an image in filtered images of the plurality of small image blocks in each sampling image. The present invention is used for solving the problems of more memory consumption and a low detection speed in the prior art.

A method for creating an overall image of an object from a plurality of recorded images that each depict a small area of the object, the method including: dividing the overall image into fields; assigning a part of the plurality of recorded images to each of the fields; and composing the plurality of recorded images into the overall image.

To sensing an anomaly on the basis of a multi-dimensional time series sensor signal, in order to determine the next action for a countermeasure, survey, or the like, the present invention is configured such that a multi-dimensional feature vector for each time is extracted on the basis of a sensor signal, a reference feature vector for each time is extracted on the basis of a set of characteristic vectors for a predetermined learning period and the characteristic vector of each time, an anomaly measure is calculated on the basis of the difference between the feature vectors for the times and the reference feature vectors, an anomaly is detected by comparing the anomaly measure and a predetermined threshold value, and the anomaly-related sensor for the time the anomaly is detected is identified on the basis of a 2-dimensional distribution density of feature values.

A method is provided for measuring or estimating stress distributions on heart valve leaflets by obtaining three-dimensional images of the heart valve leaflets, segmenting the heart valve leaflets in the three-dimensional images by capturing locally varying thicknesses of the heart valve leaflets in three-dimensional image data to generate an image-derived patient-specific model of the heart valve leaflets, and applying the image-derived patient-specific model of the heart valve leaflets to a finite element analysis (FEA) algorithm to estimate stresses on the heart valve leaflets. The images of the heart valve leaflets may be obtained using real-time 3D transesophageal echocardiography (rt-3DTEE). Volumetric images of the mitral valve at mid-systole may be analyzed by user-initialized segmentation and 3D deformable modeling with continuous medial representation to obtain, a compact representation of shape. The regional leaflet stress distributions may be predicted in normal and diseased (regurgitant) mitral valves using the techniques of the invention.

A method for processing information and an electronic device are disclosed according to the disclosure, and a display unit of the electronic device is capable of being bended with certain curvature. The method includes: once notification signal for notifying the electronic device that a first plane image needs to be displayed is received, detecting and obtaining current bending state parameters for characterizing a current bending state of the display unit based on the notification signal; acquiring the first plane image from memory; performing image processing on the first plane image according to the current bending state parameters; and transmitting the second image to video memory of the display unit, to make a projected image of the second image on a preset plane is the same as the first plane image when the second image is displayed on the display unit of the curved shape.

An image processing device includes an input unit and an alignment unit. The input unit inputs a cell shape image and a fluorescence image. The cell shape image shows a shape of a cell in a tissue section. The fluorescence image shows expression of a specific protein as a fluorescent bright point in a region same as a region in the tissue section. The alignment unit aligns the cell shape image and the fluorescence image based on an information source detected in both the cell shape image and the fluorescence image.

Provided is a feature point location estimation device, whereby fitting of a model is less prone to local solutions, and it is possible to detect a facial feature point with more practical precision. The feature point location estimation device comprises: an image input unit which receives input of a facial image from an external source; a nearest neighbor template computation unit which obtains a nearest neighbor template from among positive examples and a nearest neighbor template from among negative examples, the nearest neighbor templates being the templates nearest to an image that is computed from the inputted facial image using a facial feature point location search parameter from among a plurality of facial image templates constituted by the positive examples and the negative examples; a parameter gradient direction computation unit which computes, from the facial feature point location search parameter and the nearest neighbor templates, a gradient direction of the facial feature point location search parameter; and a search parameter update unit which updates the facial feature point location search parameter by adding the computed gradient direction.

A processing device which obtains distance information of a subject, including: a calculation unit configured to calculate the distance information of the subject from a difference in blur degree of a plurality of images photographed by an imaging optical system; a correcting unit configured to correct the distance information using correction data in accordance with an image height in the imaging optical system; and an extraction unit configured to extract at least one frequency component from each of the plurality of images, wherein the calculation unit calculates the distance information from a difference in blur degree in the plurality of images in the at least one frequency component; and the correcting unit corrects the distance information using correction data in accordance with an image height in the at least one frequency component.

In one example, a graphics processing unit may use an optimized geometric realization to render a text shape as a scalable geometry. The graphics processing unit may generate an inner geometry for a text shape. The graphics processing unit also may generate a tessellated edge geometry abutting the inner geometry for an edge of the text shape. The graphics processing unit further may assign a coverage gradient to the tessellated edge geometry to create an anti-aliased edge for the text shape.