-
ImageRetrieval
毕业设计，基于内容的图像检索，支持的检索特征包括 sift,颜色直方图，灰度矩阵，HU不变矩，边缘方向直方图，检索方法使用K-means和K-D树两种，需要OPENCV支持，运行时请先选定一个文件夹来生成特征库，特征库用access数据库保存，只支持JPG文件(Graduate design, content-based image retrieval, search features, including support sift, color histogram, gray matrix, HU moment invariants, edge direction histogram, retrieval method using the K-means and KD trees are two kinds of needs OPENCV support Please select a runtime folder to generate the feature library, feature library with access database save, only supports JPG files)
- 2010-09-14 17:31:44下载
- 积分：1
-
image_segment
最大类间方差法图像阈值分割，基于matlab平台，适用于一维二维图像分割(Otsu method of image segmentation, based on matlab platform for one-dimensional two-dimensional image segmentation)
- 2011-06-25 15:11:13下载
- 积分：1
-
superpixels.tar
超像素就是把一幅原本是像素级(pixel-level)的图，划分成区域级(district-level)的图。可以将其看做是对基本信息进行的抽象(A superpixel is a plot of a pixel level, which is divided into a regional level. Think of it as an abstraction of basic information)
- 2017-12-05 15:13:23下载
- 积分：1
-
morphological
图像的腐蚀、膨胀、开、闭运算。用菱形算子进行。(Image of erosion, dilation, opening and closing operation)
- 2020-07-03 07:40:01下载
- 积分：1
-
gaussian_average_rgb
在rgb颜色空间实现的单高斯模型，用于目标检测(In rgb color space to achieve a single-Gaussian model for target detection)
- 2009-12-13 22:56:27下载
- 积分：1
-
enhance
图像增强图像增强 对比度增强 视觉增强对比度增强 视觉增强(image Enhanceme)
- 2010-05-21 11:26:34下载
- 积分：1
-
TurboPixels
一个非常有用的超像素算法，用于图像分割,文件夹包含文章,采用matlab和c混编(a very useful superpixels algorithm，can be used for image segmentation,the file contatins paper,the matlab and c are mixed for exeution)
- 2013-01-27 11:24:08下载
- 积分：1
-
matlab
使用matlab对医学图像进行处理，不同去噪方法结果的对比。(matlab image nosing)
- 2013-04-11 21:26:37下载
- 积分：1
-
intrans
灰度变换元代码，用于matlab7.0以上版本(Picture Process)
- 2011-12-15 21:13:07下载
- 积分：1
-
liver_ultr
Abstract—Noninvasive ultrasound imaging of carotid plaques
allows for the development of plaque-image analysis methods associated
with the risk of stroke. This paper presents several plaqueimage
analysis methods that have been developed over the past
years. The paper begins with a review of clinical methods for visual
classification that have led to standardized methods for image
acquisition, describes methods for image segmentation and denoizing,
and provides an overview of the several texture-feature
extraction and classification methods that have been applied. We
provide a summary of emerging trends in 3-D imaging methods
and plaque-motion analysis. Finally, we provide a discussion of the
emerging trends and future directions in our concluding remarks.
- 2013-10-28 12:36:04下载
- 积分：1
