Description: this document shows how to normalize illumination and reducing the negative effects of illumination on face recognition. Platform: |
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Author:gawed |
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Description: 毕设时写的程序，主要是人脸识别中的光照处理方法，包括直方图均衡，对数变换，SQI，MQI，SI等。本程序基于opencv实现。-This program demonstrates some illumination normalization methods used in face recognition.Histogram equaliztion,Logarithm transform,SQI,MQI are included.This program is based on opencv. Platform: |
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Author:顾徐鹏 |
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Description: 程序结构
整个工程可以分为3个部分：算法、功能和应用。
算法部分
算法部分目前分为4个模块：人脸对齐、光照归一化、特征提取和选择、子空间降维，每个模块是一个项目，每个项目生成一个dll供功能部分显式调用。
功能部分
功能部分只有一个项目FaceMngr，该部分依赖于算法部分，实现人脸注册、训练、识别、导入/导出等具体功能。该项目生成一个dll供应用部分隐式调用。
应用部分
人脸识别Demo.
另外，工程中还有一个项目tools，实现了一些整个工程都可能用到的函数，大部分与OpenCV有关。该项目生成一个dll供各部分隐式调用。-Program Structure
The whole project can be divided into three parts: the algorithm, function and application.
algorithm part
Algorithm is part of the currently divided into four modules: face alignment, illumination normalization, feature extraction and selection, reduced subspace
Dimension, each module is a project, each project generates a dll explicitly call for the functional part.
Features section
Functional part of only one project FaceMngr, part of the part depends on the algorithm to achieve face up, training,
Recognition, import/export and other specific functions. The project generates a dll for the supply of part of the implicit call.
Application Part
Face Recognition Demo.
In addition, there is a project engineering tools, to achieve a number of projects are likely to use the function, the majority
With OpenCV related. The project generates a dll called implicitly for each part. Platform: |
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Author:吴嘉晔 |
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Description: this adaboost based real time face detection and tracking system
i used a adaboost and camshift algorithm with opencv and vc++
The detεction efficiency of the method is not good for environment of dynanlic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance.-this is adaboost based real time face detection and tracking system
i used a adaboost and camshift algorithm with opencv and vc++
The detεction efficiency of the method is not good for environment of dynanlic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. Platform: |
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Author:pattern |
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Description: 在opencv里实现局部二值算子，它是一种纹理描述算子，度量和提取图像局部的纹理信息，对光照具有不变性-Achieve local binary operator in opencv where it is a texture description operator, local measure and extract image texture information, illumination invariance Platform: |
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Author:张凌华 |
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Description: Retinex理论的基础理论是物体的颜色是由物体对长波（红色）、中波（绿色）、短波（蓝色）光线的反射能力来决定的，而不是由反射光强度的绝对值来决定的，物体的色彩不受光照非均匀性的影响，具有一致性，即retinex是以色感一致性（颜色恒常性）为基础的。不同于传统的线性、非线性的只能增强图像某一类特征的方法，Retinex可以在动态范围压缩、边缘增强和颜色恒常三个方面打到平衡，因此可以对各种不同类型的图像进行自适应的增强。-The basic theory of Retinex theory is the color of the object by object for the long wavelength (red), medium (green), short wave (blue) light reflection ability to decide, rather than by the intensity of reflected light of the absolute value to decide, the color of the object under illumination nonuniformity effects, consistent with the Retinex, that is based on color constancy (color constancy based). Different from the traditional linear, nonlinear image enhancement method of only one kind of features, Retinex can be in dynamic range compression, edge enhancement and three aspects of color constancy hit the balance, thus enhancing adaptive to a variety of different types of images can be. Platform: |
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Author:吴双 |
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Description: This an OPENCV based project. Here we are implementing the algorithm that uses adaptive
methods to segment the image to identify objects.
The objects are then used to form candidate markers which are examined for several criteria.
Potential markers are then sampled and guide information present in the marker is used to verify
the data. The algorithm is invariant to scale and rotation and is robust to motion blur and varying
illumination.-This is an OPENCV based project. Here we are implementing the algorithm that uses adaptive
methods to segment the image to identify objects.
The objects are then used to form candidate markers which are examined for several criteria.
Potential markers are then sampled and guide information present in the marker is used to verify
the data. The algorithm is invariant to scale and rotation and is robust to motion blur and varying
illumination. Platform: |
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Author:NayAlteia |
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Description: 论文源代码 ：[2013TIFS] Exposing digital image forgeries by illumination color classification-Some notes on
A) Compilation
B) Execution of the code
C) Parameters
D) General remarks on our work in color constancy and image forensics
E) Referencing the code
A) COMPILATION
To compile the code, you require
- OpenCV (tested with 2.4.0)
- Boost (tested with 1.45)
- cmake (tested with 2.8.2)
We typically built the code on a debian squeeze Linux. The build process worked
also without modifications under Ubuntu Linux.
enter the root directory of the code (illum_maps). To build the code, these steps:
snip
mk build
cd build
ccmake ../
snap
The curses interface of cmake shows up. Press c to configure. If you compiled
OpenCV on your own, cmake probably complains that it did not find OpenCV.
In this case, set the variable OpenCV_DIR to the directory in your OpenCV
installation that contains the file OpenCVConfig.cmake . This is typically
<opencv_install_dir>/share/OpenCV/
Press c to confi Platform: |
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Author:jinxiao |
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Description: 目标检测首先利用统计的方法得到背景模型，并实时地对背景模型进行更新以适应光线变化和场景本身的变化，用形态学方法和检测连通域面积进行后处理，消除噪声和背景扰动带来的影响，在HSV色度空间下检测阴影，得到准确的运动目标。(object detectWe use statistical methods to obtain the background model, and real-time of the background model is updated to adapt to illumination changes and scene changes, using morphological method and connected domain detection area of postprocessing, eliminating the background noise and the impact of disturbance, in the HSV color space under the shadow detection, moving target accurately.) Platform: |
Size: 3885056 |
Author:科研666
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Search - illumination opencv