An image processing apparatus includes a controller configured to execute: acquiring objective image data representing an objective image which includes a first character and a second character; analyzing first partial image data and specifying the first character in an image represented by the first partial image data; and generating processed image data representing a processed image which includes the first character and the second character by using the objective image data. The objective image data includes the first partial image data in a bitmap format which represents the image including the first character and second partial image data in a vector format which represents an image including the second character. The processed image data includes: first processed data representing an image including the first character; and second processed data representing an image including the second character.

The present invention discloses a method of determining a whole-scene image by using multiple image-capturing devices, and the method has two main features including non-contact formation digital image method and the parallax elimination process for captured images. The former feature uses a concyclic fitting calculation to easily determine the locations and orientations of the image-capturing devices, so as to achieve the objective of assisting in capturing the whole-scene image. The latter feature can effectively improve the image quality, so as to effectively solve the problems in conventional technology.

The present disclosure provides a system and method for PET image reconstruction. The method may include processes for obtaining physiological information and/or rigid motion information. The image reconstruction may be performed based on the physiological information and/or rigid motion information.

Disclosed is a method of changing at least one of a direction and position of a plane selection line for acquiring an image of a plane of interest of an object. The method includes acquiring a medical image of an object, displaying a first plane image acquired along a first plane selection line of the medical image, setting a pattern which is used to change at least one of the direction and position of the plane selection line, changing at least one of the direction and position of the plane selection line, based on the set pattern, and displaying a second plane image acquired along the changed plane selection line.

A method for selecting samples of reticle design data patterns in order to calibrate the parameters based on which the reference image used in a die-to-database reticle inspection method is rendered, the method comprising the steps of applying local binary pattern (LBP) analysis to a plurality of samples to obtain a p-dimensional vector output for each of the plurality of samples, clustering the q-D data points to M groups, selecting one sample from each clustered group, calculating evaluation scores for the samples selected, and, selecting a portion of the M samples on the representativeness score and the diversity score.

Examples are disclosed herein that relate to classifying ambiguous data in an image. One example provides, on a computing device, a method of processing image data, the method comprising defining a contiguous area of ambiguous data in an image, determining a border surrounding the contiguous area, classifying the contiguous area as dark or far based on a characteristic of one or more pixels of the border, and for the classified contiguous area, processing one or more pixels of the contiguous area differently if the contiguous area is classified as far than if the contiguous area is classified as dark.

Disclosed embodiments facilitate keypoint selection in part by assigning a similarity score to each candidate keypoint being considered for selection. The similarity score may be based on the maximum measured similarity of an image patch associated with a keypoint in relation to an image patch in a local image section in a region around the image patch. A subset of the candidate keypoints with the lowest similarity scores may be selected and used to detect and/or track objects in subsequent images and/or to determine camera pose.

A flow meter includes an image sensor and a processor. The image sensor is configured to capture an image of a drip chamber. The processor is configured to determine whether the captured image of the drip chamber contains a match to a template, and to apply a blurring function to the image captured by the image sensor of the drip chamber such that the processor can determine if the captured image contains a match to the template.

A flow meter includes a first image sensor, a background pattern, and at least one processor. The first image sensor has a first field of view and is positioned to view a drip chamber within the first field of view. The background pattern is positioned within the field of view of the first image sensor, and the background pattern includes first and second portions. The processor is operatively coupled to the first image sensor and configured to: receive a first image from the first image sensor, and estimate at least one parameter of liquid within the drip chamber in accordance with a distortion of the background pattern caused by the liquid as indicated by the first image.

Subject matter herein can include identifying a biochemical test strip assembly electrically, such as using the same test circuitry as can be used to perform an electrochemical measurement, without requiring use of optical techniques. The identification can include using information about a measured susceptance of an identification feature included as a portion of the test strip assembly. The identification can be used by test circuitry to select test parameters or calibration values, or to select an appropriate test protocol for the type of test strip coupled to the test circuitry. The identification can be used by the test circuitry to validate or reject a test strip assembly, such as to inhibit use of test strips that fail meet one or more specified criteria.