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Skull extraction from Magnetic Resonance (MR) head image datasets is the process of segmentation of brain tissues from other tissues (e.g., skin, bone, fat) and has an important role in computer-assisted operations. Because, the accuracy of skull extraction affects the next stages of digital image processing or analysis. Semi-/full automated detection and extraction of the skull from MR datasets is...
The Image Foresting Transform (IFT) is a general framework to develop image processing tools for a variety of tasks such as image segmentation, boundary tracking, morphological filters, pixel clustering, among others. The Differential Image Foresting Transform (DIFT) comes in handy for scenarios where multiple iterations of IFT over the same image with small modifications on the input parameters are...
Text segmentation is an important problem in document analysis related applications. We address the problem of classifying connected components of a document image as text or non-text. Inspired from previous works in the literature, besides common size and shape related features extracted from the components, we also consider component images, without and with context information, as inputs of the...
Real-time Magnetic Resonance Imaging (rtMRI) leads to the dynamic observation of hidden processes of articulation in an unprecedented way. The non-invasive image acquisition nature of MRI combined with enhanced anatomical discrimination made rtMRI the reference in capturing vocal tract configurations during speech production. However, this development also unveiled challenges, such as the shape extraction...
Sign language automatic recognition is an important research area with open challenges that aims to mitigate the obstacles in the daily lives of people who are deaf or hard of hearing and increase their integration in the predominantly hearing society in which we live. This paper implements, evaluates and discusses strategies for automatic recognition of Brazilian Sign Language (BSL) signs, which...
We propose a novel diminished reality method which is able to (i) automatically recognize the region to be diminished, (ii) work with a single RGB-D sensor, and (iii) work without pre-processing to generate a 3D model of the target scene by utilizing SLAM, segmentation, and recognition framework. Especially, regarding the recognition of the area to be diminished, our method is able to maintain high...
Atherosclerosis is a disease responsible for millions of deaths each year, primarily due to heart attack and stroke. Magnetic resonance (MR) imaging is a non-invasive method that can be used to analyze the carotid artery and detect signs of atherosclerosis. Most MR methods acquire high contrast, static images. These methods, however, are sensitive to artifacts from cardiac motion, produce time-averaged...
This paper introduces a new method for multiobject segmentation in images, named as Hierarchical Layered Oriented Image Foresting Transform (HLOIFT). As input, we have an image, a tree of relations between image objects, with the individual high-level priors of each object coded in its nodes, and the objects' seeds. Each node of the tree defines a weighted digraph, named as layer. The layers are then...
The quality of life of people is increasing together with the developing technologies. One of the most important factors affecting daily life is smart cities. The quality of life of people is positively affected by emerging this concept in recent years. Autonomous vehicles confront with the term of the smart city and have become even more popular in recent years. In this study, a system of traffic...
In this study, segmentation of medical images is implemented by an edge-based level set approach based on the client-server communication. In the method, a medical image, which is already loaded into the image gallery of the smartphone by the user, is selected, the pathological region to be segmented is roughly marked and then both the input image and the marked region, and some input parameters used...
This paper presents a general framework for live detection of broilers in poultry houses. The challenges for image recognition of broilers are posted by crowded scenes, poor image quality and difficulty in acquiring a benchmark of labeled samples. The proposed framework consists on the use of image thresholding, morphological transformations, feature engineering, in addition to supervised and unsupervised...
Multiple Sclerosis (MS) is a neurological, progressive widespread disease whose diagnosis, treatment and monitoring have vital importance. However, manual method based on visual inspection for diagnosis and time-series assessments of changes in MS lesions is not re-producible and quantitative. Also, it is subjective and yields in inter-/intra-observer variabilities. Furthermore, the conventional method...
Most of the existing methods achieve co-saliency detection at single level. In this work, we combine the object-level and region-level processing to detect co-salient objects in a group of images. At the object level, we formulate proposal selection as an outlier detection problem. We find good region proposals and generate a template for each image. At the region level, we introduce the smoothness...
The frequent occurrence of road congestion and traffic accidents has affected people's travel efficiency and travel safety. Traffic sign recognition has become one of the key research objects in intelligent transportation system. This paper studies the identification of road traffic signs based on video images. First of all, collected image will be image preprocessing with image reduction, brightness...
Potato as the fourth largest staple food in China, The external defect detection directly affects the industrialization of potato and deep processing. As the currently domestic testing method are mostly based on specific circumstances, specific light, which does not satisfy the testing requirements of actual environment. Therefore, this paper presents a non-destructive method for the study of green,...
We report on the results of the first visual search and rating study (N60) evaluating human gaze when assessing the realism of image composites. The effects of object identity knowledge and mismatched feature type on observers' gaze and subjective realism scores are studied. Gaze metrics used include: fixation count, fixation duration, time and duration of first fixation on target object, as well...
The purpose of the paper is to add solutions to the recognition and transport of minerals copper mining in southern Ecuador, using tools that have MATLAB® and LabVIEW®. The algorithm developed in MATLAB® using the principles of image processing to segment and filters the same. Finally applies the theory of neuro-fuzzy for the recognition of the presence of copper in a rock that is modeled. Is important...
This paper presents an automatic detection system capable of detecting an automobile dashboard with high accuracy. Since the structure of an automobile dashboard is quite different from general instruments, commonly used algorithms for instrument detection can hardly meet the accuracy and robustness. In this paper, a novel approach is presented to detect an automobile dashboard. The contour retrieving...
A post-processing method for correcting the beam hardening artifacts in fan beam axial computed tomography is presented. The original uncorrected CT image is reconstructed using filtered backprojection algorithm. Image segmentation technique is adopted to exact the high density object from the uncorrected CT image. The original and high density image are reprojected individually. Certain correction...
Digital image processing techniques are commonly employed for food classification in an industrial environment. In this paper, we propose the use of supervised learning methods, namely multi-class support vector machines and artificial neural networks to perform classification of different type of almonds. In the process of defining the feature vectors, the proposed method has relied on the principal...
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