A performance study of image segmentation techniques

Image based applications such as target tracking, tumor detection, texture extraction requires an efficient image segmentation process. The partitioning of image into various non- overlapping distinct regions refers the image segmentation. Various segmentation techniques like edge, threshold, region, clustering and neural network are involved in the effective image analysis. The efficiency of the segmentation process improved with the help of several algorithms, namely, active contour, level set, Fuzzy clustering and K-means clustering. This paper analyses the performance of algorithms for image segmentation in detail. Intensity and texture based image segmentation is the two levels of the level set method. The combination of both intensity and texture based image segmentation provides better results than the traditional methods. The detailed survey of segmentation techniques provides the requirement of the suitable enhancement method that supports both intensity and texture based segmentation for better results. The comparison between the traditional image segmentation techniques are illustrated.

[1]  Hossein Mobahi,et al.  Segmentation of Natural Images by Texture and Boundary Compression , 2011, International Journal of Computer Vision.

[2]  Ian D. Reid,et al.  Nonlinear shape manifolds as shape priors in level set segmentation and tracking , 2011, CVPR 2011.

[3]  Sim Heng Ong,et al.  A new unified level set method for semi-automatic liver tumor segmentation on contrast-enhanced CT images , 2012, Expert Syst. Appl..

[4]  K. K. Rahini,et al.  Review of Image Segmentation Techniques: A Survey , 2014 .

[5]  Jasjit S. Suri,et al.  Automatic Lung Segmentation Using Control Feedback System: Morphology and Texture Paradigm , 2015, Journal of Medical Systems.

[6]  Salem Saleh Al-amri,et al.  Image Segmentation by Using Threshold Techniques , 2010, ArXiv.

[7]  Hongbao Cao,et al.  Segmentation of M-FISH Images for improved classification of chromosomes with an adaptive fuzzy c-means clustering algorithm , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[8]  Nor Ashidi Mat Isa,et al.  Color image segmentation using histogram thresholding - Fuzzy C-means hybrid approach , 2011, Pattern Recognit..

[9]  DeLiang Wang,et al.  Remote Sensing Image Segmentation by Combining Spectral and Texture Features , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Jianfei Cai,et al.  Constrained active contours for boundary refinement in interactive image segmentation , 2012, 2012 IEEE International Symposium on Circuits and Systems.

[11]  Daniel Cremers,et al.  A Linear Framework for Region-Based Image Segmentation and Inpainting Involving Curvature Penalization , 2011, International Journal of Computer Vision.

[12]  Boying Wu,et al.  Local- and Global-Statistics-Based Active Contour Model for Image Segmentation , 2012 .

[13]  T. Arivoli,et al.  Brain tumor segmentation and its area calculation in brain MR images using K-mean clustering and Fuzzy C-mean algorithm , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[14]  Qiang Chen,et al.  Fuzzy Local Gaussian Mixture Model for Brain MR Image Segmentation , 2012, IEEE Transactions on Information Technology in Biomedicine.

[15]  Marek Kretowski,et al.  A Texture-Based Energy for Active Contour Image Segmentation , 2014, IP&C.

[16]  Yann LeCun,et al.  Road Scene Segmentation from a Single Image , 2012, ECCV.

[17]  Max W. K. Law,et al.  Segmentation of Intracranial Vessels and Aneurysms in Phase Contrast Magnetic Resonance Angiography Using Multirange Filters and Local Variances , 2013, IEEE Transactions on Image Processing.

[18]  Maoguo Gong,et al.  Fuzzy C-Means Clustering With Local Information and Kernel Metric for Image Segmentation , 2013, IEEE Transactions on Image Processing.

[19]  Bostjan Likar,et al.  A Game-Theoretic Framework for Landmark-Based Image Segmentation , 2012, IEEE Transactions on Medical Imaging.

[20]  Dwarikanath Mahapatra,et al.  Integrating Segmentation Information for Improved MRF-Based Elastic Image Registration , 2012, IEEE Transactions on Image Processing.

[21]  Anant Madabhushi,et al.  Multifeature Landmark-Free Active Appearance Models: Application to Prostate MRI Segmentation , 2012, IEEE Transactions on Medical Imaging.

[22]  Yizhou Yu,et al.  Interactive Image Segmentation Based on Level Sets of Probabilities , 2012, IEEE Transactions on Visualization and Computer Graphics.

[23]  Pieter Abbeel,et al.  A textured object recognition pipeline for color and depth image data , 2012, 2012 IEEE International Conference on Robotics and Automation.

[24]  Nor Ashidi Mat Isa,et al.  Automated two-dimensional K-means clustering algorithm for unsupervised image segmentation , 2013, Comput. Electr. Eng..

[25]  Wei-Yun Yau,et al.  Multichannel Pulse-Coupled-Neural-Network-Based Color Image Segmentation for Object Detection , 2012, IEEE Transactions on Industrial Electronics.

[26]  Michalis A. Savelonas,et al.  Unsupervised 2D gel electrophoresis image segmentation based on active contours , 2012, Pattern Recognit..

[27]  Lauge Sørensen,et al.  Texture-Based Analysis of COPD: A Data-Driven Approach , 2012, IEEE Transactions on Medical Imaging.

[28]  Chunming Li,et al.  A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application to MRI , 2011, IEEE Transactions on Image Processing.

[29]  Nico Karssemeijer,et al.  Segmentation of the Pectoral Muscle in Breast MRI Using Atlas-Based Approaches , 2012, MICCAI.

[30]  Marios S. Pattichis,et al.  Fast Localization and Segmentation of Optic Disk in Retinal Images Using Directional Matched Filtering and Level Sets , 2012, IEEE Transactions on Information Technology in Biomedicine.

[31]  Alfred O. Hero,et al.  Graph based k-means clustering , 2012, Signal Process..

[32]  M. A. Balafar,et al.  Gaussian mixture model based segmentation methods for brain MRI images , 2012, Artificial Intelligence Review.

[33]  Yunmei Chen,et al.  An Efficient Algorithm for Multiphase Image Segmentation With Intensity Bias Correction , 2013, IEEE Transactions on Image Processing.

[34]  Jesmin F. Khan,et al.  Image Segmentation and Shape Analysis for Road-Sign Detection , 2011, IEEE Transactions on Intelligent Transportation Systems.

[35]  Jie Shan,et al.  Building roof modeling from airborne laser scanning data based on level set approach , 2011 .