搜索资源列表
04
- 研究了基于视频图像处理的自行车流量检测方法，主要方法为利用二值化的“时空图像”计算1 像素块儿的个数。给出了各种方法对自行车流量检测的实验结果。-Research on video image processing based on the flow of bicycle detection methods, the main method for the use of binarization of " time and space images," Calculation
tuxiangshibie
- 用帧差分可以检测场景变化，一个简单帧差分可通过计算两个连续帧的象素获得。对帧内每个象素点（x,y），T时刻与T－1时刻象素值之差为Dx,y(T)=||Sx,y(T) – Sx,y(T-1)||。设定内帧差分系数IDsum=ΣL , IF ||Sx,y(T) – Sx,y(T-1)||≥Ta THEN L=TRUE，实际决定是否报警,可以通过计算三帧以上IDsum数量-Frame difference can be detected with the scene changes, a simple
shipinjiance
- 由于光线的影响,两帧图象中的物体无运动,但灰度稍微有变化,这种情况也会影响检测的准确度,所以对两帧图象的象素点进行比较时,可以让它们相减的差值和某个小的数值比较,而不一定就是和0值比较-As the effect of light, two images of an object without moving, but the gray has changed slightly, this will also affect the accuracy of detection, so the tw
CGLGrassfire
- OpenCV function that finds BLOBS in a binary image with the help of the Grassfire algorithm. It is not recursive, but call the function Grassfire each time a white pixel is found in the image. Input: 8bit Unsigned Char binary image. Output: Ch
segmention
- 4连通指的是从区域上一点出发，可通过4个方向，即上、 下、左、右移动的组合，在不越出区域的前提下，到达区域内的任意像素； 8连通方法指的是从区域上一点出发，可通过左、 右、上、下、左上、右上、左下、右下这8个方向的移动组合来到达区域内的任意像素。
A_barycenter_based_fast_thinning_algorithm
- 分析快速细化算法和 OPTA 细化算法不足产生的内在原因 ,提出一种新的基于重心的快速细化算法.该算 法根据被细化图像的特点 ,用密度重心快速将纹线细化到 3 个像素宽度内 ,计算 4 邻域拓扑实现彻底细化.仿真结 果表明 ,在细化效率方面 ,该算法一次遍历删除超过一半的大量冗余像素 ,是快速细化算法的 3～7 倍 在细化要求 方面 ,该算法可达到绝对单像素、 光滑无毛刺 ,并能保持端点不被吞噬 ,能够很好地满足图像细化的要求. -The int rinsic origin of
On-the-Removal-of-Shadows-From-Images
- This paper is concerned with the derivation of a progression of shadow-free image representations. First we show that adopting certain assumptions about lights and cameras leads to a 1-d, grey-scale image representation which is illuminant inva
12864LCD
- 这是一个可以精确到像素级的JM12864G的LCD头文件，用户可以使用里面的API完成这样的功能：把某个图片显示在屏幕坐标系的任意位置，超出屏幕部分不显示，不自动换行，而不只是在纵坐标上具体到像素级，而横坐标只能是“第几个字”的位置-This is an accurate to pixel level JM12864G the LCD header file, the user can use inside the API to accomplish this function: to an i
Hyperspectralunmixing-technique
- 研究非监督的高光谱图像混合像元的解混技术研究-Hyperspectral images in the case of non-supervision of mixed pixel unmixing technique
bmp-process
- bmp格式显示,包括其头文件，信息头，像素值读取，及操作处理-bmp format, including its header file header, the pixel value reading, and processing operations
active-contour
- The region is iteratively grown by comparing all unallocated neighbouring pixels to the region. The difference between a pixel s intensity value and the region s mean, is used as a measure of similarity. The pixel with the smallest difference measure
region-growing
- egion growing approach is the opposite of the split and merge approach: An initial set of small areas are iteratively merged according to similarity constraints. Start by choosing an arbitrary seed pixel and compare it with neighbouring pi
Seed-Filling
- 平面区域填充算法是计算机图形学领域的一个很重要的算法，区域填充即给出一个区域的边界（也可以是没有边界，只是给出指定颜色），要求将边界范围内的所有象素单元都修改成指定的颜色（也可能是图案填充）。区域填充中最常用的是多边形填色，本文中我们就讨论几种多边形区域填充算法。-The planar area filling algorithm is a very important algorithms in the field of computer graphics, area fills, i.e.
wsiearth
- ArcGIS开发使用 世界地图 TIFF 分辨率：10020*5010 大小：47.87 MB 空间参考：D_WGS_1984 像素深度：8 位 -The ArcGIS Developer resolution World Map TIFF: 10020* 5010 size: 47.87 MB spatial reference: D_WGS_1984 Pixel Depth: 8
kmeans_report
- 数据挖掘kmeans图像聚类实验报告 用 VC 或 Java 实现 k-means 聚类算法， 分别以迭代次数及分配不再发生变化为算法终止条件，用图片（自己选择）作为数据集，比较运行时间（画出时间与像素点的关系曲线图，因此须用多幅像素个数不同的图片进行实验） 提交实验报告与源代码。 -Data mining to achieve the k-means clustering algorithm the kmeans image clustering experiment report wit
The-image-pixel-matching
- 基于像素匹配的图像“复制-粘贴”篡改检测算法,简单易懂-The image pixel matching "copy-paste" tamper detection algorithm based on, easy to understand
TraceRay
- 从视点出发，通过图像平面上每个像素中心向场景发出一条光线，光线的起点为视点，方向为像素中心和视点连线单位向量。-From the viewpoint of, for each pixel on the image plane through the center to the scene issued a light of a starting point for the viewpoint direction pixel center and the viewpoint connection
Pixel-level-Image-Fusion-Algorithms-for-Multi-cam
- this doc is very much helpful for learning image fusion at pixel level
COSMO-SkyMed
- cosmo-skymed合成孔径雷达SAR系统的数据介绍：包括成像模式，刈幅宽度，分辨率，像元间隔，极化方式，入射角等详细信息。-Data cosmo-skymed SAR synthetic aperture radar system descr iption: For more information, including imaging mode, swath width, resolution, pixel spacing, polarization, incidence angle.
Differce-pixel-value
- Difference pixel embedded and extract code for matlab