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展示了汽车行业的应用案例。任务是利用标定的可变形匹配来定位不同方向和位置的车门(3D variable model matching)

卷积神经网络深度学习，可以识别多种图像，并自动解出所需要的结果(Deep learning of convolutional neural networks)

基于数学形态学实现振动信号降噪。研究了数学形态滤波器对振动信号在不同类型、不同强度噪声干扰下 的降噪能力，提出了采用开一闭和闭一开组合数学形态滤波器实现旋转机械振动信号降噪处理的方法。通过仿真 计算及实例，检验了形态滤波器的滤波效果，表明数学形态滤波器可以有效剔除脉冲、降低随机噪声干扰，提高 振动信号的信噪比。(The vibration signal noise reduction based on mathematical morphology. Mathematical morphology filter vibration signals in different types, different intensity noise, noise reduction capabilities, proposes using open-closing and close the opening combination of mathematical morphology filter rotating machinery vibration signal noise reduction processing. Simulation and examples, test the morphological filters filtering effect, indicating that the mathematical morphological filter can effectively excluded the pulse, to reduce random noise and improve the signal-to-noise ratio of the vibration signal.)

基于DCT的数字水印抗滤波性能检测matlab代码(DCT-based digital watermarking anti-filtering performance detection matlab code)

介绍了一种显著性检测，程序可以直接运行，可以得到显著图像，有图像源。(propose a bottom-up visual saliency detection algorithm. Different most previous methods that mainly concentrate on image object, we take both background and foreground into consideration. )

简单图像捕获源码程序，结合易语言数码设备支持库，调用API函数发送消息使数码设备捕获图像。(Simple image capture source program, combined with easy language digital equipment support library , call the API function to send a message so that digital devices to capture images.)

基于Kalman滤波和Meanshift算法的目标跟踪算法的C++程序，运行可用，具有参考价值。(The C++ program of target tracking algorithm based on Kalman filter and Mianshift algorithm is available and has reference value.)

本科毕设要求参见标准测试模型，均值便宜跟踪的示例，利用最小二乘算法实现对三维平面的拟合。( Undergraduate complete set requirements refer to the standard test models, Example tracking mean cheap, Least-squares algorithm to fit a three-dimensional plane.)

霍夫曼图像压缩编码，无损压缩，压缩率为2倍，压缩效果很好。(Image compression Huffman coding, lossless compression, the compression rate is 2 times the compression works well.)

基于边界约束和上下文正则化的图像快速去雾算法(Effi cient Image Dehazing with Boundary Constraint and Contextual)