wanglang3081的专栏

In this chapter, we will cover:   Accessing pixel values   Scanning an image with pointers  Scanning an image with iterators   Writing efficient image scanning loops   Scanning an image with neig

The distribution of pixels value across the image constitutes an important characteristic of this image. that's the concept discript as histograms.A histogram is a simple table that gives the numbeer

Goal In this chapter We will see an intuitive understanding of SVM Theory Linearly Separable Data Consider the image below which has two types of data, red and blue. In kNN, for a test

in the case of a Gaussian filter, the weight associated with a pixel is proportional to its distance from the central pixel. Recall that the 1D Gaussian function has the following form: G(x)=Ae^(

http://docs.opencv.org/doc/tutorials/imgproc/histograms/back_projection/back_projection.html?highlight=normalize http://docs.opencv.org/modules/core/doc/operations_on_arrays.html?highlight=normalize#

What is an Image Histogram? It is a graphical representation of the intensity distribution of an image.It quantifies the number of pixels for each intensity value considered. What is Histo

Examples Small image The following is the same 8x8 subimage as used in JPEG. The 8-bit greyscale image shown has the following values: The histogram for this image is shown in the following tab

Goal In this tutorial you will learn how to: Use the OpenCV function morphologyEx to apply Morphological Transformation such as: OpeningClosingMorphological GradientTop HatBlack Hat

ntroduction The work with a cascade classifier inlcudes two major stages: training and detection.Detection stage is described in a documentation of objdetect module of general OpenCV documentation.

Goal In this tutorial you will learn how to: Use the OpenCV functions CvSVM::train to build a classifier based on SVMs and CvSVM::predict to test its performance. What is a SVM? A Su

Goal In this tutorial you will learn how to: Define the optimization problem for SVMs when it is not possible to separate linearly the training data.How to configure the parameters in CvSVMPar

HSV(Hue, Saturation, Value)是根据颜色的直观特性由A. R. Smith在1978年创建的一种颜色空间, 也称六角锥体模型(Hexcone Model)。 这个模型中颜色的参数分别是：色调（H），饱和度（S），亮度（V）。 HSV颜色空间模型[1] 色调H：用角度度量，取值范围为0°～360°，从红色开始按逆时针方向计算，红色为0°，绿色为120°,

In this tutorial you will learn how to: Apply two very common morphology operators: Dilation and Erosion. For this purpose, you will use the following OpenCV functions: erodedilate Cool The