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We have proposed a new speckle filtering method in this paper. Our method uses time-series of SAR images at the same scene to perform multitemporal speckle filtering to reduce speckle noise while preserving its spatial information. We used segmentation based on the distribution of speckle noise by the Öztürk algorithm in this method for achieve a higher quality of edge areas.
We propose a new method for fitting an ellipse to a point sequence extracted from an image. This method can fit an ellipse if a point sequence consists of elliptic arcs and non-elliptic arcs such as line segments. Assuming that input points are spatially connected, we iteratively select inlier points and fit an ellipse to them by computing curvatures of the residual graph. By using simulated data...
This paper deals with development of Robust Moving Object Detection method using Visible Spectrum and Thermal Imaging. If we fuse visible spectrum and Thermal imaging together, more information about the moving object can be obtained as both are inherently complementary to each other. The segmentation of moving objects in corresponding video frames involves ‘Background Subtraction’ method. Here each...
We introduce a technique for extracting the vessel structure in the fundus image of a retina. Retinal vessel segmentation achieved by categorizing every pixel belonging to vessel structure or not, derived from characteristic vector consisting of the gray level values and coefficients of 2-D Gabor wavelet at various scales. Specific frequency tuning of Gabor wavelet allows vessel segmentation even...
Despite recent advances, robust automatic segmentation for vertebrae computed tomography (CT) image still presents considerable challenges, mainly due to its inherent limitations, such as topological variation, irregular boundaries (double boundary, weak boundary) and image noises, etc. Therefore, this paper proposes a novel automatically initialized level set approach based on region correlation,...
Finger vein is a new and promising trait in biometric recognition and some related progress have been achieved in recent years. Considering that there are many different sensors in a biometric system, sensor interoperability is a very important issue and still neglected in the state-of-the-art finger vein recognition. Based on the analysis of the shortcomings in the current finger vein ROI extraction...
The appearance of masses in in X-ray mammograms is one of the early signs of women breast cancer. Currently, mammography is the single most effective and reliable technique in the investigation of breast abnormalities detection such as masses. However, their detection is still a challenging problem due, to the diversity in shape, size, ambiguous margins and to the poor contrast between the cancerous...
Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorders affected to female in their reproductive cycle. PCO (Polycystic Ovaries) describes ovaries that contain many small cysts/follicles. This paper proposes an image clustering approach for follicles segmentation using Particle Swarm Optimization (PSO) with a new modified non-parametric fitness function. The new modified fitness function...
Mammography is currently the most efficient imaging technique employed in radiology for examining breast cancer. Searching for a suitable, flexible and efficient breast profile segmentation method has been shown to be a herculean task in digital mammography. The extraction of the breast profile region is a fundamental pre-processing step in computer- aided detection of breast cancer. Principally,...
Underwater image segmentation is a key step for the analysis of the underwater target as segmentation quality will directly affect the stability and reliability of target recognition and tracking. A novel segmentation method is proposed in this paper that can help to solve the edge expansion and contour deformation problems in traditional segmentation methods. Firstly, the dark channel prior algorithm...
A spatially constrained kernel fuzzy C-means (SCKFCM) algorithm is represented for polarimetric SAR (PolSAR) remote sensing image segmentation in this paper. Compared with classic fuzzy C-means (FCM) algorithm, kernel method could perform the nonlinear mapping from the original space to kernel space. Thus, SCKFCM is not impacted by the remote sensing image data distribution. Furthermore, in order...
In this work, we present a latent fingerprint segmentation algorithm based on spatial-frequency domain analysis. The algorithm arranges the overlapped block-based Fourier coefficients into groups of frequency and orientation subbands, called Rearranged Fourier Subband (RFS). The RFS reveals latent fingerprint spectra in only a limited number of subbands. The algorithm then boosts, sorts, and extracts,...
This paper describes a new segmentation-based classification technique for fully polarimetric synthetic aperture radar (PolSAR) images. Based on the framework which conjunctively uses statistical region merging (SRM) for segmentation and support vector machine (SVM) for classification, we improve the method by jointly introducing texture features and color features. For the segmentation step, to guarantee...
Boron carbide microscopie images may present grains crossed by twins (or macles) viewed as straight lines in the inner part of each grain. The twins preclude the segmentation because they are very similar to the grain borders. To eliminate the twins a preprocessing step, which relies on mathematical morphology tools, is applied to the image. The main operation used is a directional opening, using...
In this paper, a Markov Random Field (MRF)-based method is presented. MRF methods are based on a probabilistic representation of a image processing problem; the problem is represented as the maximization of a probability measure computed starting from input data for all possible solutions. The optimization process is often computationally expensive. The coupled problem of restoring and extracting...
This contribution deals with the textured images segmentation. The model exploits morphological operators and order filters properties. A morphological decomposition filters bank is built to isolate elementary patterns by decomposing the textural image characteristics. The 1 and 2 order statistic moments and the gradient means are computed in order to select the best feature component image which...
Positron emission tomography (PET) is capable of capturing the functional information. A major limitation for PET imaging is the low spatial resolution, leading to partial volume effects (PVE). PVE introduces significant bias to the image quantification, causing compromised measurement for uptake regions, especially smaller ones. For quantitative PET, accurate uptake values are critical for diagnostic...
For robust segmentation of white matter lesions (WML), a partial volume fraction (PVF) estimation approach was previously developed for FLAIR MRI that does not depend on predetermined intensity distribution models or multispectral scans. Instead the PV fraction was estimated directly from each FLAIR MRI using an adaptively defined global edge map that exploits a novel relationship between edge content...
Ultrasound (US) data suffer from speckle noise as well as intensity inhomogeneities due to underlying changes in acoustic properties of tissue structure and/or the effects of acoustic focusing and attenuation. This paper describes a 2D and 3D variational level-set method for segmenting such data. To deal with the local statistics of speckle noise, the data term of the level-set energy function is...
Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary...
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