Vocabulario ingles percepcion

VOCABULARIO PERCEPCIÓN

RAFAEL LINARES PRIETO

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Computer vision: is a subfield of artificial intelligence. The purpose of the vision is to program a computer to "understand" a scene or the characteristics of an image. Machine vision: is a branch of engineering that uses computer vision in the context of manufacturing. Imageacquisition: it is about acquiring digital images from devices that are used primarily in still image capture, such as scanners and digital cameras, and transferring those images to the user computer. Tracking: the maintenance of a constant difference in frequency between connected circuits or components. Segmentation: process which separates the relevant from the irrelevant to a particular application.Pattern recognition: image processing phase in which a label is assigned to the elements detected. Sampling: analog image subdivision into portions. Quantification: conversion of light intensity at discrete values. Discretization: concerns the process of transferring continuous models and equations into discrete counterparts. Optical centre: A point on the axis of a lens so that, for any raypassing through this point, the incident part and the emergent part are parallel. Focal length: is a measure of how strongly the system converges (focuses) or diverges (defocuses) light. Translation: Geometric transformation that maps the position of each pixel in the input image to a new position in the output image. Rotation: Transformación geométrica la cual mapea la posición de un píxel de unaimagen de entrada en una posición a una imagen de salida por rotación de la misma a través de un ángulo especificado por el usuario y un origen. Scale: Geometric transform used to compress or enlarge the size of an image. Homogeneus coordinates: are a system of coordinates used in projective geometry much as Cartesian coordinates are used in Euclidean geometry. Disparity: a great difference. Neighbor:something situated next to or very near. Connectivity: capacity for the interconnection of platforms, systems, and applications. Euclidean distance: between points p and q is the length of the line segment connecting them. Manhattan distance: computes the distance that would be traveled to get from one data point to the other if a grid-like path is followed. The Manhattan distance between twoitems is the sum of the differences of their corresponding components. Filtering: a piece of software that processes data before passing it to another application, for example, to remove unwanted material. Mask: matrix we use on an image to allow selective modification of the underlying material. Mask size: dimensions of a mask. Grey level: A calibrated sequence of grey tones, ranging from black towhite. Threshold: is the simplest method of image segmentation. From a grayscale image, thresholding can be used to create binary images.

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Background: part of an image that lies outside the object(s) of interest captured by the image. Foreground: the part of a scene or representation that is nearest to and in front of thespectator. Normalized histogram: Indicate the frequency of occurrence of gray level and is calculated as P (nk) = nk / n, where nk the number of color pixels k and n the total number of pixels of the image. Cumulative histogram: Considering the above definition of the histogram, then you can get the cumulative histogram of the image as the sum of these probabilities. Smooth: having an even andregular surface; free from projections or indentations. Mean: is a method to derive the central tendency of a sample space. Average: mean synonymous. Noise: is the random variation of brightness or color information in images produced by the sensor and circuitry of a scanner or digital camera. Salt and peeper: is a form of noise typically seen on images. It represents itself as randomly occurring...