搜索结果: 1-6 共查到“计算机应用 Clustering”相关记录6条 . 查询时间(0.078 秒)
Performance analysis of EM-MPM and K-means clustering in 3D ultrasound breast image segmentation
segmentation EM-MPM ultrasound
2015/1/20
Mammographic density is an important risk factor for breast cancer, detecting and screening at an early stage could help save lives. To analyze breast density distribution, a good segmentation algorit...
基于KFCM和改进分水岭算法的猪肉背最长肌分割技术（Segmentation of Pork Longissimus Dorsi Based on KFCM Clustering and Improved Watershed Algorithm）
无损检测 图像分割 猪肉
2010/1/28
提出一种利用核模糊C均值聚类（KFCM）和改进分水岭算法分割猪肉眼肌切面图像中背最长肌区域的方法。该算法对经中值滤波去噪后图像的R分量利用最大方差自适应阈值（OTSU）去除背景，再采用KFCM提取出肌肉组织，然后进行空洞填充，最后由改进的分水岭算法分割出背最长肌区域。利用该算法对采集的60幅猪肉眼肌图像进行处理，分割正确率为86.67%；与传统的形态学算法相比，该算法能真实、完整地恢复出背最长肌区...
基于PSO与K-均值算法的农业超绿图像分割方法（Agriculture Extra-green Image Segmentation Based on Particle Swarm Optimization and K-means Clustering）
图像分割 微粒群算法 K均值算法
2009/9/11
为了解决K-均值算法对农业图像中常用的超绿特征2G—R—B图像分割效果不佳的缺点，提出一种基于微粒群与K均值算法的图像分割方法。先用K均值算法对图像进行快速分类，然后将分类结果作为其中一个微粒的结果，利用微粒群算法计算，最后用K-均值算法在新的分类基础上计算新的聚类中心，更新当前的位置，以得到最优的图像分割阈值。试验结果表明，改进算法对超绿特征2G—R—B图像能够准确分割目标，且对不同类型的农业超...
An Algorithm for Image Clustering and Compression
Image segmentation Image compression Fuzzy clustering
2009/7/28
This paper presents a new approach to image compression based on fuzzy clustering. This new approach includes pre-filtering, and fuzzy logic image enhancing to reduce undesirable noise effects on segm...
Hierarchical Background Subtraction using Local Pixel Clustering
Hierarchical Background Subtraction Local Pixel Clustering
2013/7/17
We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our ...
CLUSTERING-BASED SUBSPACE SVM ENSEMBLE FOR RELEVANCE FEEDBACK LEARNING
image retrieval relevance feedback data clustering classifier sampling SVM classifier ensemble
2013/7/17
This paper presents a subspace SVM ensemble algorithm for adaptive relevance feedback (RF) learning. Our method deals with the case that user’s relevance feedback examples are usually insufficient and...