ellipse-detection-algorithm

说明：  简单的颜色特征提取程序，可以提取RGB图像中的特征向量(Simple color feature extraction)

各种音频数字水印源代码，有详细的代码解释说明。dct，dwt等(Audio digital watermark source code, detailed code explanation. dct, dwt)

利用 计算机强大的图像生成功能，快速、便捷地模拟生成实际战场环境下可能经历的 各种红外场景，逼真地反映探测制导系统的红外辐射分布(Using powerful computer image generation, quickly and easily simulate actual battlefield environment generated may experience a variety of infrared scene vividly reflect the guidance system to detect infrared radiation distribution)

这是一个去背景并且进行阈值分割的程序，阈值的选择采用迭代法(This is the background to a threshold value and segmentation procedures, the threshold value of the options using the iterative method)

高光谱图像MNF算法，实现高光谱图像的去噪，注释详尽(Hyperspectral image MNF algorithm to achieve denoising hyperspectral images, detailed comments)

说明：  非常详细的一篇论文，仔细介绍了手指静脉识别的的全过程(A very detailed paper, carefully introduced the finger vein identification process)

利用回转窑生产氧化铝的工艺中，提出了一种新的基于SVR（支持向量回归）的烧成带温度软测量方法。即首先对从回转窑采集到的烧结图像进行预处理，消除噪声的干扰；然后利用大津方法分割出物料区和火焰区，并提取这些区域的图像特征；其次利用基于SVR方法建立的烧成带温度模型计算温度值；参数计算.(The use of alumina rotary kiln production process, a new-based SVR (support vector regression) of the burning zone temperature soft measurement method. That is first collected from the rotary kiln sintering image pre-processing to eliminate noise interference Otsu method and then use the materials division of the district and flame zones, and extraction of image features in these regions SVR-based method followed by the establishment of the burning zone temperature model temperature parameters.)

图像时频变换实例，包括FFT变换、FFT逆变换、DCT变换、DCT逆变换、DWT变换、DWT逆变换、WHT变换、WHT逆变换等。(Examples of image frequency conversion, including FFT transform, FFT transform, DCT transform, DCT transform, DWT transform, DWT transform, WHT transform, inverse transform, etc..)

通过将高分辨率的图像和低分辨率的图像进行融合，来实现图像的融合。(By fusing high-resolution and low-resolution images, image fusion can be achieved.)

三个很好的程序，有染色体的识别，车牌跟踪，还有神经网络设计，肯定是非常好的，希望大家从中学习(Three very good procedures, there are chromosome recognition, license plate tracking, as well as neural network design, is certainly very good, I hope you learn from)