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We have developed techniques to automatically generate personalised biomechanical models of patients' hearts based on 3D cardiac images. We demonstrate this approach using multi-slice computed tomography images. Unsupervised segmentation was performed using non-rigid image registration with a segmented image. A finite element model was automatically fitted to the segmented data of the left ventricle...
We propose a fully automatic method to segment the dentate nucleus using diffusion weighted images (DWI). Initialization of the dentate nucleus is produced by combining the information from tractography results on the diffusion tensor images (reconstructed from DWI) and b0 images. A geometric de-formable model (GDM) with generalized gradient vector flow (GGVF) is then applied on the b0 image to generate...
Increased frequency of micronuclei is positively correlated with the molecular dosimetry of genotoxic damages. The cytokinesis-block micronucleus test (CBMN test) is a well-established assay used in toxicological screening for potential genotoxic compounds. Since the method is simple and economical, CBMN assay can be employed on a large scale as a quantitative biological dosimeter. Automated detection...
Segmentation problem dates back to a couple of decades and many solutions have been proposed so far. The fact that there is still no solution with optimum performance justifies the efforts towards new studies. This study concentrates on keeping the user interaction in the loop for superior results. Proposed technique extends previous knowledge on monoscopic image segmentation to stereoscopic footage...
Color image segmentation is a critical pre-process in image processing. Also it's important in the field of computer vision and pattern recognition. In this paper, we first state some evidence in the human vision research. Not all the intensity from 0 to 255 in RGB spaces can be distinguished by human vision. So we reduce the level of the intensity in RGB space to 26,28,26 respectively, while maintaining...
Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic...
In this paper, we propose a system to obtain a depth ordered segmentation of a single image based on low level cues. The algorithm first constructs a hierarchical, region-based image representation of the image using a Binary Partition Tree (BPT). During the building process, T-junction depth cues are detected, along with high convex boundaries. When the BPT is built, a suitable segmentation is found...
Biometric systems have been implemented on numerous public facilities that able to enhance the security system. Nowadays, fingerprint and face are the most popular biometric. In addition, emerging technology has introduced potential biometric such as hand geometry, palm print, lips, teeth and vein. However, most of this biometric requires a special device to capture it. This will added more cost to...
Biometrics systems based on ear are still in need of more investigation to make it robust and accurate. The most critical step in ear recognition is segmentation as all subsequent steps will depend on the accuracy of segmentation. In this paper, a robust ear segmentation method is suggested. The proposed method consists of a sequence of steps. First, a Biased Normalized Cuts method is applied to initiate...
In this paper, we use a segmentation method applied to the plants images analysis. The segmentation gives groups of pixels, and we propose to use merging operators to address the most relevant groups in order to improve the recognitions systems performance. In particular, we use an operator called fully reinforced. The experiments carried out show that the use of improves outcomes for structuring...
Normalised cuts algorithm requires massive similarity measurement computation for image segmentation. Since a digital camera at present has the capability to produce high resolution image, it will be inevitably that resizing image into suitable resolution at which the algorithm can perform image segmentation with minimal burden. While retaining the important features in the images, natural images...
Enormous agricultural yield is lost every year, due to rapid infestation by pests and insects. A lot of research is being carried out worldwide to identify scientific methodologies for early detection/identification of these bio-aggressors. In the recent past, several approaches based on automation and image processing have come to light to address this issue. Most of the algorithms concentrate on...
In this paper, we propose a new region-based saliency model to simulate the human visual attention. First, we construct a pixel-level fully-connected graph representation for an image, and perform normalized cut to segment the image based on the proximity and similarity principles. After obtaining image regions, we reconstruct a region-based fully-connected graph. Based on the saliency principle “center-surround...
This paper presents a simple and effective method to compute the pixel saliency with full resolution in an image. First, the proposed method creates an image representation of four color channels through the modified computation on the basis of Itti et al.[5]. Then the most informative channel is automatically identified from the derived four color channels. Finally, the pixel saliency is computed...
This paper addresses a novel head posture detection algorithm to recognize human-computer interactions. A pattern training based image segmentation algorithm is used to detect the skin and hair of students. A simple and efficient human presence detection and gaze direction estimation method is then proposed based on the segmentation results. Finally, the proposed algorithm is tested on ten different...
Seeded segmentation methods attempt to solve the segmentation problem in the presence of prior knowledge in the form of a partial segmentation, where a small subset of the image elements (seed-points) have been assigned correct segmentation labels. Common for most of the leading methods in this area is that they seek to find a segmentation where the boundaries of the segmented regions coincide with...
This paper deals with automatically segmenting a person from challenging videos using a pose detector. A state of the art pose detector is used to detect the pose of a person from a frame in the video sequence. The pose is used to extract color and optical flow features to train a conditional random field to provide segmentation on multiple frames. Location from the pose is used to refine the results...
In this paper we propose a color-based approach for skin detection and interest garment selection aimed at an automatic segmentation of pieces of clothing. For both purposes, the color description is extracted by an iterative energy minimization approach and an automatic initialization strategy is proposed by learning geometric constraints and shape cues. Experiments confirms the good performance...
We propose an image sharpening method that automatically optimizes the perceived sharpness of an image. Image sharpness is defined in terms of the one-dimensional contrast across region boundaries. Regions are automatically extracted for all natural scales present that are themselves identified automatically. Human judgments are collected and used to learn a function that determines the best sharpening...
One goal of projector-camera system is let human finger be used like a mouse to click and drag objects in the projected content. It requires segmentation of the human palm and fingers in the image data captured by the camera, which is a challenging task in the presence of the incessant variation of the projected video content and the shadow cast by the palm and fingers. We describe a coarse-to-fine...
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