A quantification system (300) is described that includes: at least one input (310) configured to provide at least one input medical image and provide a location of interest in the at least one input medical image; and a mapping circuit (325). The mapping circuit (325) is configured to: compute a direct quantification result from the location of interest of the at least one input medical image to a quantification of interest and output a direct first quantification result therefrom; generate a saliency map as part of the computation of the direct quantification result; and derive a segmentation from the saliency map, such that the segmentation independently generates a second quantification result that is within a result range of the direct first quantification result.

The present disclosure provides a method and device for determining a handwriting similarity. The method includes: performing image processing on a handwriting image comprising a handwriting to be compared to obtain a first processed image and a second processed image having different handwriting features of the handwriting image; determining, based on the first processed image, a first feature vector indicating at least one first handwriting feature of the handwriting to be compared; determining, based on the second processed image, a second feature vector indicating at least one second handwriting feature of the handwriting to be compared; determining a handwriting feature vector of the handwriting to be compared based at least on the first feature vector and the second feature vector; and determining a similarity between the handwriting to be compared and a reference handwriting based on the handwriting feature vector and a reference handwriting feature vector of the reference handwriting.

Embodiments of the present disclosure provide a text detection method and apparatus, and a storage medium. The method includes: obtaining edge information of a to-be-detected image; and determining candidate text pixels in the to-be-detected image according to the edge information of the to-be-detected image by using a preset candidate text pixel determining strategy. The method also includes performing projection based segmentation on the candidate text pixels to obtain a projection based segmentation result. The method also includes determining one or more text regions in the to-be-detected image according to the projection based segmentation result.

When conducting imaging mass analysis for a region to be measured on a sample, an individual reference value calculating part obtains a maximum value in P.sub.i/I.sub.i of respective measuring points, and stores the value together with measured data as an individual reference value. When performing comparison analysis for a plurality of the data obtained from different samples, a common reference value determining part reads out corresponding a plurality of the individual reference values and determines a minimum value as a common reference value Fmin. A normalization calculation processing part normalizes the respective intensity values by multiplying the intensity values read out from an external memory device by a normalization coefficient long_Max(Fmin/P.sub.i) obtained from the common reference value Fmin, TIC values Pi at the respective measuring points, and a maximum allowable value long_Max of a variable storing the intensity values at the time of operation.

A computer-implemented method, a computer system and a non-transitory computer-readable medium for constructing human-readable sentences from imaging data of a subject can include: receiving imaging data including image elements of at least one region of interest of the subject; segmenting the imaging data of the region of interest into a plurality of sub-regions, where each sub-region includes a portion of the image elements; calculating an abnormality factor for each of the sub-regions by quantitatively analyzing segmented image information of the imaging data of the sub-regions using data from a normal database; comparing each abnormality factor to a threshold value; constructing a human-understandable sentence for the subject when a corresponding abnormality factor exceeds the threshold, where each human-understandable sentence references a physical structure threshold associated with the calculation for the region or sub-region; and outputting the human-understandable sentences for the at least one region of the subject.

A method for acquiring traffic sign information includes acquiring an image of a scene comprising a traffic sign, the image being obtained by photographing the scene, using a photographing apparatus, acquiring first laser data of the scene, the first laser data being obtained by performing laser scanning on the scene, and the first laser data being of a plurality of first laser points, performing spatial clustering on the plurality of first laser points to obtain candidate point sets, acquiring a spatial distribution feature of respective laser points in each of the candidate point sets, determining at least one point set corresponding to the traffic sign in the candidate point sets, based on the spatial distribution feature, extracting image data of the traffic sign, from the image, using the at least one point set corresponding to the traffic sign, and extracting sign information of the traffic sign, from the image data.

Systems, devices, media, and methods are presented for receiving a set of images in a video stream, converting one or more images of the set of images to a set of single channel images, generating a set of approximation images from the set of single channel images, and generating a set of binarized images by thresholding the set of approximation images.

The present invention relates to a method to generate a slap/fingers foreground mask to be used for subsequent image processing of fingerprints on an image acquired using a contactless fingerprint reader having at least a flash light, said method comprising the following steps: acquisition of two images of the slap/fingers in a contactless position in vicinity of the reader, one image taken with flash light on and one image taken without flash light, calculation of a difference map between the image acquired with flash light and the image acquired without flash light, calculation of an adaptive binarization threshold for each pixel of the image, the threshold for each pixel being the corresponding value in the difference map, to which is subtracted this corresponding value multiplied by a corresponding flashlight compensation factor value determined in a flashlight compensation factor map using an image of a non-reflective blank target acquired with flash light and to which is added this corresponding value multiplied by a corresponding background enhancement factor value determined in a background enhancement factor map using the image acquired without flash light, binarization of the difference map by attributing a first value to pixels where the adaptive binarization threshold value is higher than the corresponding value in the difference map and a second value to pixels where the adaptive binarization threshold value is lower than the corresponding value in the difference map, the binarized image being the slap/fingers foreground mask.

Embodiments of the present application relate to a method, apparatus, and system for detecting a specified image identifier. The method includes retrieving a target image to be detected from a predetermined area, binarizing the target image to be detected to obtain a target binary image to be detected, calibrating connected domains of the target binary image to be detected, successively retrieving image features of candidate connected domains, and comparing the image features corresponding to the candidate connected domains to image features of a standard specified identifier image, wherein the candidate connected domains are determined based at least in part on the calibration of the connected domains, and determining a candidate connected domain as the location of the specified identifier image based at least in part on the comparison of the image features corresponding to the candidate connected domains to image features of the standard specified identifier image.

A face recognition method and apparatus, the method comprising: capturing a first image, the first image including a face content of a user and a background content; adjusting a relative position between an image capture device and the user; capturing a second image after the relative position is adjusted, the second image comprising a second face content of the user and a second background content; comparing the face content and the background content in the first image with those in the second image respectively and obtaining difference information; and determining that the user is an authentic user or an impostor according to the difference information. According to embodiments of the present application, the problem that current face liveness detection methods fail in recognizing impostors can be solved.