Analysis of Random Projection & Live - Wire For Texture Extraction & Segmentation

Pradnya A. Maturkar; M.A.Gaikwad

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Analysis of Random Projection & Live - Wire For Texture Extraction & Segmentation

机译：纹理提取和分割随机投影和活丝分析

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Automatic image segmentation requires a certain degree of depth of work combining image clustering, feature extraction, statistical analysis and iterative feedback. Researchers have been using algorithms like Principal component analysis (PCA) combined with advanced feature extraction techniques like gray level co-occurrence integrated algorithm (GLCIA), along with maximal difference schemes (MDS), have been proposed by researchers, and provide good quality of semi-automatic segmentation. But in these techniques, user intervention is needed in at least 1 of the steps in order to get a proper output. This work proposes a RP-live wire based algorithm which optimizes the segmentation process, and removes the user intervention from the segmentation process in order to produce high quality segmented images with truly automatic segmentation. Our results demonstrate a 20% improvement in overall system speed and 10% improvement in segmentation accuracy when compared with traditional algorithms.

机译：自动图像分割需要一定程度的工作深度，相结合图像聚类，特征提取，统计分析和迭代反馈。研究人员一直使用像主成分分析（PCA）这样的算法，与高级特征提取技术相结合，如灰度共同发生集成算法（GLCIA），以及通过研究人员提出的最大差分方案（MDS），并提供了良好的品质半自动分割。但是在这些技术中，在至少1个步骤中需要用户干预，以便获得适当的输出。这项工作提出了一种基于RP-Live导线的算法，其优化了分割过程，并从分割过程中删除了用户干预，以产生具有真正自动分割的高质量分段图像。与传统算法相比，我们的结果表明整体系统速度的提高20％和分割精度的10％提高。

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《IOSR journal of electrical and electronics engineering》 |2018年第6期|共5页
作者
Pradnya A. Maturkar; M.A.Gaikwad;
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作者单位

Dept. Electronics Engineering RGCE Nagpur RTM University;

Dept. Electronics &

Telecommunication Engineering GHRCE Nagpur RTM University;

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原文格式 PDF
正文语种 eng
中图分类电工技术;
关键词
GLCIA; GMTD; live-wire; MDS; PCA;

机译：GLCIA;GMTD;Live-Wire;MDS;PCA;

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1. Analysis of Random Projection & Live - Wire For Texture Extraction & Segmentation [J] . Pradnya A. Maturkar, M.A.Gaikwad IOSR journal of electrical and electronics engineering . 2018,第6期

机译：纹理提取和分割随机投影和活丝分析
2. Morphological Segmentation Analysis and Texture-based Support Vector Machines Classification on Mice Liver Fibrosis Microscopic Images [J] . Wang Yu, Shi Fuqian, Cao Luying, Current Bioinformatics . 2019,第4期

机译：形态学分割分析和基于纹理的支持向量机在小鼠肝纤维化微观图像上进行分类
3. Interactive segmentation based on the live wire for 3D CT chest image analysis [J] . Kongkuo Lu, William E. Higgins International Journal of Computer Assisted Radiology and Surgery . 2007,第3a4期

机译：基于实时导线的交互式分割，用于3D CT胸部图像分析
4. Directional analysis of image textures for feature extraction and segmentation [C] . Kontaxakis, I., Sangriotis, Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on . 2003

机译：图像纹理的方向分析，用于特征提取和分割
5. Unsupervised segmentation of noisy and textured images modeled by Markov random fields. [D] . Gregoriou, Georghios Kyriacos. 1992

机译：由Markov随机场建模的噪点和纹理图像的无监督分割。
6. Whole-liver CT texture analysis in colorectal cancer: Does the presence of liver metastases affect the texture of the remaining liver? [O] . Sheng-Xiang Rao, Doenja MJ Lambregts, Roald S Schnerr, 2014

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Analysis of Random Projection & Live - Wire For Texture Extraction & Segmentation

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