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Echocardiography provides information about size, shape, and function of heart to create the image. Apical four-chamber echocardiography can be obtained by placing the ultrasound probe at the apex of the left ventricle. Such view enables to analyze heart abnormalities. In this regard, chamber quantification is recommended to evaluate the heart volume by defining the endocardial border of the chambers...
Image segmentation is an important task in computer vision. The task of image segmentation is to portion image into segments, thus provide more meaningful information of the image contents. Many methods have been developed for numerous application. The common problems of most of the segmentation techniques are scattered segmentation lines, too much details, small or thin segments, and noisy segmentation...
This paper presents the results of the HDSRC 2014 competition on handwritten digit string recognition in challenging datasets organized in conjunction with ICFHR 2014. The general objective of this competition is to identify, evaluate and compare recent developments in Western Arabic digit string recognition with varying length. In addition, this competition introduces two new challenging datasets...
Video tools developed today, teachers can record lecture videos and upload these lecture videos to e-learning system themselves. However, some students may only do not understand some fragments but they have to waste unnecessary time download entire video, and therefore video scene segmentation is relative importance. In addition, in traditional teaching model, students must listen and transcribe...
Microarray is one of the most promising tools available for researchers in the life sciences to study gene expression profiles. Through microarray analysis, gene expression levels can be obtained, and the biological information of a disease can be identified. The gene expression information embedded in the microarray is extracted using image-processing techniques. Gridding is one of the important...
In this paper, we propose a fast and efficient method to extract skin and bone automatically. First, we smooth the images by applying anisotropic diffusion filter to remove noise. Then, the whole body is detected by using thresholding which is set automatically. In addition, we segment the contour of the skin by using morphological operators and connected component labeling (CCL). Finally, we extract...
This paper presents a method to automatic segmentation of cervical intraepithelial neoplasia (CIN3) parabasal cervical cells from PAP Smear images. The proposed method based on the structural characteristics of cervical; the region of nucleus by using Active Contour Model (ACM). The energy function is minimized in order to correct the less gradient of image energy area; to correct the cloudy contour...
The low-level line segment features have low accuracy as they are more easily affected by the noise and differeent line segment detectors. Furthermore, the line segment is not a good feature for matching across multiple views when we need to finish the 3D reconstruction. However, the line feature is more robust for the noise. In this paper, a kind of line feature, ideal line, is defined and optimally...
In wireless network, the resource limitations and process speed are the main constraints. They make many traditional background subtraction methods unable to be applied in wireless network. Vibe algorithm is a newly proposed background subtraction technique and its computational load is very low. That makes it available in the wireless network. However, Vibe is a pixel-level algorithm and it does...
In this paper, a novel technique is proposed based on fuzzy logic reasoning for edge detection in medical Magnetic Resonance (MR) brain image. The MR image is segmented into regions using 2×2 binary matrices. In our proposed work, it is possible to detect the edge without determining the threshold values. The ranges of values are mapped by the edge pixels distinct from each other. The Fuzzy Inference...
A new shadowed c-means clustering based image segmentation method is proposed in this paper. By including the local spatial information in shadowed c-means algorithm and mapping the original data into a high dimensional space via kernel method, we propose the Kernel Spatial Shadowed C-Means (KSSCM) clustering algorithm for image segmentation problems. The KSSCM based approach shows better performance...
Blur metrics have been used in broad range of applications to quantify the amount of blur especially in images. The spatially varying blur due to defocus or camera shake is hard to estimate. It is observed that the existing blur metrics does not perform well for images having very few or many features. In this work, we present contrast based blur invariant features named as CBIF, which utilizes useful...
One of the most commonly used methods for Magnetic Resonance Imaging (MRI) segmentation is Fuzzy C-Means (FCM). This method in comparison with other methods preserves more information of the images. Because of using the intensity of pixels as a key feature for clustering, Standard FCM is sensitive to noise. In this study in addition to intensity, mean of neighbourhood of pixels and largest singular...
Line detection in gray-scale images is a low-level processing which has many applications such as road detection in remote images and vessel detection in medical images. An efficient primitive connection-based algorithm for detecting line segments is proposed. Canny operator is used to detect edges in a digital image and all the edges are tracked to form series of edge point chains by a 4-neighbor-priority...
To extract quantitative and shape information of blood cells from micrograph images, good segmentation of these images is essential. In this paper, a method Based on the geodesic active contour (GAC) is proposed for such task. The Gaussian filtering working for edge detection in GAC is replaced with wavelet-package filtering, which enable the GAC cope better with noise disturbance and finally lead...
In this paper, we present a technique to recognize books from library bookshelf images. The proposed technique includes several modules such as — noise removal, bookshelf row detection and book detection and extraction from bookshelf. Firstly, the image is filtered for noise removal and edges are detected. The proposed technique counts the number of pixels of every candidate for horizontal lines on...
OTSU method is considered to be the best algorithm for image segmentation of threshold selection. It's very simple and it's regardless of image brightness and contrast effects. Therefore it has been widely used in digital image processing. However, in the actual image, because of the influence of noise etc., traditional OTSU algorithm cannot be obtained an accurate segmentation results. In this paper,...
Nowadays, hand vein recognition is amongst the most recent biometric technologies used for the identification/authentication of individuals. Indeed, hand veins biometric are robust and steady human authentication unlike to other biometric technologies as fingerprint, face, signature and voice. In the present work, the proposed system consists of image preprocessing, feature extraction and identification...
Semantic mapping is a long term goal to understand environment for mobile robots. The indoor environments usually consist of a large amount of planar surfaces. Thus, plane segmentation is an essential prerequisite to build a semantic map. In this paper, we develop an algorithm to segment planar surfaces from noisy point clouds of indoor scenes. The proposed segmentation algorithm is based on a graph-based...
Automatic accurate segmentation methods are needed to assess longitudinal cartilage changes in osteoarthritis (OA). We propose a novel general spatio-temporal three-label segmentation method to encourage segmentation consistency across time in longitudinal image data. The segmentation is formulated as a convex optimization problem which allows for the computation of globally optimal solutions. The...
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