Abstract:
L'invention concerne un procédé de production et/ou de contrôle d'une pièce en matériaux composites formée à partir d'au moins un tissu ayant une surface dont la texture présente une orientation principale, comportant les étapes suivantes: -obtenir une première image représentant la texture du tissu; -déterminer une estimation relative à l'orientation principale de la texture, en: déterminant, pour chaque pixel de la première image, une orientation de gradients relatifs au niveau de luminance dudit pixel; déterminant une estimation d'une distribution globale des orientations de gradients des pixels de la première image; déterminant l'orientation principale en fonction de l'estimation de la distribution globale des orientations de gradients des pixels de la première image; -déterminer un écart entre l'estimation relative à l'orientation principale et une valeur de consigne; -produire la pièce en fonction de l'écart et/ou émettre un signal de contrôle fonction de l'écart.
Abstract:
A liveness-detection method and/or system is disclosed. A method of detecting liveness can comprise obtaining a single ultrasonic image of a biometric object. The single ultrasonic image can be subdivided into a plurality of overlapping sample blocks. Feature vectors can be extracted in a spatial domain and a frequency domain from each of the plurality of sample blocks. The feature vectors can be compared from each of the plurality of sample blocks to a classification model.
Abstract:
An image processing method, includes: obtaining an image, the image having marker images and a background image; identifying presence of an object in the background image using a processor; and providing a signal for stopping a procedure if the presence of the object is identified. An image processing apparatus, includes: a processor configured for: obtaining an image, the image having marker images and a background image; identifying presence of an object in the background image; and providing a signal for stopping a procedure if the presence of the object is identified.
Abstract:
Ex vivo cell culture, especially the culture of stem cells, is a valuable and widely used technique. The appearance of unlabeled cultured cells contains significant information about the cell's identity, including its differentiation status and lineage. However, mere visual inspection of cells is a subjective process subject to inconsistencies between microscopists. This disclosure provides methods of quantifying cells' appearance, validating identity with known biomarkers, allowing automated classification of cells as well as automated segmentation and delineation of the borders of a cell colony. Also provided are systems and methods for comparing and standardizing cells cultured by different scientists using different cell culture methods.
Abstract:
In an embodiment, a device comprises a plurality of elements configured to apply a filter to multiple groups of pixels in a neighborhood of pixels surrounding a particular pixel to generate a matrix of filtered values; compute, from the matrix of filtered values, a first set of gradients along a first direction and a second set of gradients along a second and different direction; determine how many directional changes are experienced by the gradients in the first set of gradients and the gradients in the second set of gradients; compute a first weighted value for a first direction and a second weighted value for a second direction; and based, at least in part, upon the first and second weighted values, compute an overall texture characterization value for the particular pixel, wherein the overall texture characterization value indicates a type of image environment in which the particular pixel is located.
Abstract:
Apparatus for and a method of processing sensor data, the method comprising: using a sensor (4), measuring values of a parameter over a region of interest (12) to produce an image of the region of interest, the image comprising a plurality of pixels; for each pixel, determining an orientation of a gradient of the parameter, at that pixel, using the measured parameter values; for each of a plurality of predetermined ranges of gradient orientation values, determining a number of pixels that have a gradient orientation value within that range; identifying the predetermined ranges that correspond to a number of pixels above a threshold value; and for each identified predetermined range, identifying as corresponding to a feature of an object, pixels that have gradient orientation values within that predetermined range.
Abstract:
Local histogram and local histogram based functions can be determined by generating offset kernel images based on domain shifted tonal filter kernels. The offset kernel images are reusable for multiple image locations and/or local neighborhood sizes, shapes, and weights. A neighborhood filter representing the desired local neighborhood size, shape, and frequency domain characteristics is applied to the offset kernel images. Neighborhood filters may include a temporal dimension for evaluating neighborhoods in space and time. Neighborhood filtered offset kernel images' values represent samples of local histogram or local histogram based function corresponding with the domains of their associated domain shifted tonal filter kernels. Tonal filter kernels may be arbitrary functions. Local histogram functions' values may be sampled with a histogram kernel. A tonal filter kernel that is a derivative or integral of another tonal filter kernel may be used to sample a derivative or integral, respectively, of a function.