Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction and training of models, computational approaches to efficient implementation, and parallel implem
Histogram equalization is a method in image processing of contrast adjustment using the image's histogram. Assume that the original image gray level r normalized in between 0 and 1, 0 ≦r ≦1. pr(r) is the probability density function of the original
Otsu’s method of image segmentation selects an optimum threshold by maximizing the between-class variance in a gray image. However, this method becomes very time-consuming when extended to a multi-level threshold problem due to the fact that a large
This book is about detecting and recognizing 2D objects in gray-level images. Howare models constructed? Howare they trained? What are the computational approaches to efficient implementation on a computer? And finally, how can some of these computa
Algorithm Descr iption Recognizing objects from large image databases, histogram based methods have proved simplicity and usefulness in last decade. Initially, this idea was based on color histograms that were launched by swain [1]. This algorithm p
a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training set.
Brightness Preserving Dynamic Fuzzy Histogram Equalization(BPDFHE) proposes a novel modification of the brightness preserving dynamic histogram equalization technique to improve its brightness preserving and contrast enhancement abilities while redu
This paper presents a variation of fuzzy c-means (FCM) algorithm that provides image clustering. The proposed algorithm incorporates the local spatial information and gray level information in a novel fuzzy way. The new algorithm is called fuzzy loc
However, in the case of classes, you should be careful and not return image class attributes. Here is an example of an error-prone implementation: class Test { // image attribute cv::Mat ima; public: // constructor creating a gray-level image Test()
用去图像增强的一种常用方法，本资源基于论文Gray-level grouping (GLG) an automatic method for optimized image contrast Enhancement-part I the basic method实现，c++编程实现，需要opencv环境
主要介绍图像的复原技术 以下是其中的一小部分代码 function g = intrans(f, varargin) %INTRANS Performs intensity (gray-level) transformations. % G = INTRANS(F, 'neg') computes the negative of input image F. % % G = INTRANS(F, 'log', C, CLASS) computes C*log(1 + F) and % mult
各种新算法研究，没有足够的数学和英语基础就别下载了。 Artificial Intelligence and Soft Computing: 17th International Conference, ICAISC 2018, Zakopane, Poland, June 3-7, 2018, Proceedings, Part I (Lecture Notes in Computer Science) The two-volume set LNAI 10841 and LNAI 10842
Reducing Gray-Level Response to One Frame:Dynamic Capacitance Compensation。A novel driving scheme, named Dynamic apacitance Compensation (DCC), for active-matrix (AM) LCDs was developed. It takes the charge-&-hold nature of AM-LCDs into consideratio
基于Matlab直方图Histogram的人脸识别程序-Processed histogram based Face Recognition.part1.rar 基于Matlab 直方图Histogram的人脸识别程序 因为数据库图片太大，所以分成几个压缩文件。 Face recognition 原理介绍： matlab12.jpg Recognizing objects from large image databases, histogram based methods have prov
