搜索资源列表
histogram_balltracker
- A new concept of tracking ball has been applied of detecting the ball in one frame by finding centroid ball ,finding histogram of the ball region and correlating it with candidate s histogram (by scanning the complete image) in subsequent frames. Mat
singularitydetection
- 提出一种两阶段的奇异点检测方法。将指纹图像分块，求出各块的方向构成块方向图，并在块方向图的基础上利用邻域方向的分 布分析结合改进的Poincare Index方法来确定奇异点所在的候选区域，对候选区域中的像素再通过计算局部方向变化率来确定奇异点的精 确位置。将此方法用于对FVC2004 DB1_A指纹数据库的图像，实验结果表明这种方法对指纹图像中的噪声有很好的鲁棒性，并且计算简 单快速，易于实现。 -A two-phase singularity detection. Finge
FFSM
- 浮动顺序搜索算法搜索特征空间生成候选子集-Sequential floating search algorithm to search a subset of the feature space generated candidate
orientation
- 车牌定位：对侯选区域加以判别,侯选区域的判定可以利用车牌区域固有的特征来进行-License Plate Location: identification of candidate regions to be, to determine candidate regions of license plate can be used to carry out the inherent characteristics of
Ipso
- 提出了一种基于改进型微粒群算法的无线传 感器网络分簇路由算法来优化分簇过程。簇首节点的选取综合考虑候选节点和邻居节点的状态信息-Proposed a modified particle swarm algorithm based on wireless sensor network clustering routing algorithm to optimize the clustering process. Cluster head node, considering the select
pso
- In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population
code
- Minhashing和LSH算法。用于查找和比较一个pair是否是相似的。并分析false negative和false positive的值-Minhashing and Locality-Sensitive-Hashing (LSH). The algorithms are approximate in that they find only candidate pairs that are likely similar. Therefore, there are two types of
candgen
- Generates candidate set for the D-Optimal design.
IDMA
- IDMA同步情况下的系统仿真，AWGN信道，IDMA是4G的候选编码之一，译码复杂度非常小-IDMA synchronization system simulation case, AWGN channel, IDMA is one of 4G candidate code, the decoding complexity is very small
IDMA_asynchronization
- IDMA异步情况下的系统仿真，AWGN信道，IDMA是4G的候选编码之一，译码复杂度非常小-IDMA system simulation asynchronous case, AWGN channel, IDMA is one of 4G candidate coding, decoding complexity is very small
Plate-recognition-system-source-code
- 本源码是基于MATLAB实现车牌识别并语音播报。 本系统针对家庭小型车蓝底白字车牌进行识别。根据彩色图像的RGB比例定位出近似蓝色的候选区域。但是由于RGB三原色空间中两点间的欧氏距离与颜色距离不成线性比例，在设定蓝色区域的定位范围时不能很好的控制。因此造成的定位出错是最主要的。这样在图片中出现较多的蓝色背景情况下识别率会下降，不能有效提取车牌区域。对此本文提出了自适应调节方案。对分割出来的区域进行识别调整。根据长宽比，蓝白色比对候选区域进行多次定位。最终找到车牌区域。 对字符正确识别之
PSO
- Matlab PSO In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having
A-Ball-Tracking-Application
- The application uses the approach introduced in paper Covariance Tracking using Model Update Based on Means on Riemannian Manifolds , F.Porikli, O.Tuzel, P.Meer. The tracking is based on: 1) initializing the target region 2) constructing the
Software-IA-03-Particle-swarm-optimization-em-Mat
- In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.
DE
- In computer science, differential evolution (DE) is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Such methods are commonly known as metaheuristics as they make few
PSO
- In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population
Connected-Component-based-text-region-extraction.
- The basic steps of the connected-component text extraction algorithm are given below, and diagrammed in Figure 10. The details are discussed in the following sections. 1. Convert the input image to YUV color space. The luminance(Y) value is used
Edge-based-text-region-extraction-from-natural-im
- The basic steps of the edge-based text extraction algorithm are given below 1. Create a Gaussian pyramid by convolving the input image with a Gaussian kernel and successively down-sample each direction by half. (Levels: 4) 2. Create directiona
matlab
- 基于meanshift的单目标跟踪算法实现 说明： 1. RGB颜色空间刨分，采用16*16*16的直方图 2. 目标模型和候选模型的概率密度计算公式参照上文-Meanshift based single target tracking algorithm Descr iption: 1. RGB color space plane points, using a histogram 2. Probability density target model and the candid
Candidate-Elimination-Algorithm-Implementation-in
- Machine learning - candidate elimination algorithm.