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We propose a method for precise point-based see-through visualization in which feature regions are highlighted. And by using this method we can recognize the 3D structures of the cultural heritage clearly. The recent rapid development of laser scanners has enabled the precise measurement of real cultural heritage objects. In the measurement, we acquire a point cloud consisting of a large scale of...
Tuberculosis (TB) is a major health threat in the developing countries. Many patients die every year due to lack of treatment and error in diagnosis. Developing a computer-aided diagnosis (CAD) system for TB detection can help in early diagnosis and containing the disease. Most of the current CAD systems use handcrafted features, however, lately there is a shift towards deep-learning-based automatic...
Detection of repetitive patterns in images is subject of several research papers. The majority of them deals with detection of lattice patterns of repetitive elements. However, there are many situations, when element's repetition doesn't follow any particular pattern. In this paper we focus on the following two objectives. Firstly, our algorithm detects repetitive elements regardless of their relative...
Computer Aided Diagnostic (CAD) tools for differentiating benign and malignant lesions are primarily of great importance. Most of the CAD tools employ a large and complex feature set. In this paper, a CAD system for classifying benign and malignant lesions using optimal feature set is proposed. The optimal feature set included the prominent color, shape and texture features. The feature set used is...
Red blood cell count plays a vital role in identifying the overall health of the patient. Mature Red blood cells undergo morphological changes when blood disorder exists. Automated and Manual techniques exist in the market to count the number of RBCs(Red blood cells). Manual counting involves the use of Hemocytometer to count the blood cells. The conventional method of placing the smear under a microscope...
Nature has surrounded us with lot of plants having medicinal values. But most of the time, we don't realize the importance and benefits of the plant and we just ignore it. In other cases, though we know names of the plants with medicinal values, it becomes difficult to identify the plant even if it is naturally grown in our backyard. And hence, a system is developed which would provide a solution...
Many animal species exist in this world and there are always new species being discovered each year. Therefore, it is very important that these valuable species be documented properly to be referred to in future. Numerous information retrieval systems for managing and documenting animal species today only allow users to search animal images and descriptions online via text-based input. Therefore,...
This paper presents an automated computer vision system of shape defect detection for product quality inspection and monitoring system. Soft drink bottle is used as a tested product for the proposed system. The analysis framework includes data collection, pre-processing, morphological operation, feature extraction, and classification. Morphological operation technique is used to segment the image...
People who died because of natural disaster, airplane crash or vehicle accident are hard to identified. There are many parameters that used by forensic doctor to identify victims corpes. Bone is one of parameters that used by doctors to identify victims age, it provide accurate result compared to other diagnoses. But, it takes a long time for the doctors to identify manually. From those problems,...
Clustering is a well-recognized data mining technique which enables the determination of underlying patterns in datasets. In electric power systems, it has been traditionally utilized for different purposes like defining customer load profiles, tariff designs and improving load forecasting. Some surveys summarized different clustering techniques which were traditionally used for customer segmentation...
Real-time image processing on low cost embedded systems is still a challenging research area. For this embedded platform, there is a trade-off between accuracy and processing time. We proposed a pedestrian detection method for thermal images that can perform in real-time on a Raspberry Pi embedded system while still keeping the accuracy high. Our detection framework is based on the conventional HOG-based...
This paper addresses the problem of pedestrian detection in high-density crowd images, characterized by strong homogeneity and clutter. We propose an evidential fusion algorithm which is able to exploit multiple detectors based on different gradient, texture and orientation descriptors. The evidential framework allows us to model the spatial imprecision arising from each of the detectors. A first...
In this paper, we propose a two-step textural feature extraction method, which utilizes the feature learning ability of Convolutional Neural Networks (CNN) to extract a set of low level primitive filter kernels, and then generalizes the discriminative power by forming a histogram based descriptor. The proposed method is applied to a practical medical diagnosis problem of classifying different stages...
Recent background subtraction methods use fusion of multiple features to achieve consistent performance in non-stationary environment. During the segmentation, most of these methods apply logical operators (AND, or OR) to the results of each observed feature. Using logical operators has two critical problems, e.g. i) AND operator may reduce true-positives, and ii) OR operator may increase false-positive...
Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis or simply M. tuberculosis. It is primarily an infection of lungs, but it can also affect other parts of the body such as brain, intestine, kidney and spine. TB remains one of the leading cause of death in developing countries, although most are preventable if diagnosed early and treated. Among the available...
The emerging field of graph signal processing has brought new scope in understanding the spectral properties of arbitrary structures. This paper proposes a novel graph spectral domain feature representation scheme for recognising in-air drawn numbers. It provides the solution by forming the hand's path as a graph and extracting its features based on the spectral domain representation by computing...
Facial expression recognition is an active research area in the field of signal social processing. The goal is to distinguish human emotion. The problem is similar emotion, variation of emotion, and independent object through face image. The existing research using various method for modeling human facial to entirely describe facial expression through face image. We consider to variation analysis...
Interactive robotics is a vast and expanding research field. Interactions must be sufficiently natural, with robots having socially acceptable behavior by Humans, adaptable to user expectations. Thus allowing easy integration in our daily lives in various fields (science, industry, health, etc). Natural interaction during Human-Robot collaborative action needs suitable interaction techniques. In our...
Ultrasound image is one of the modalities that is widely used to examine the abnormality of thyroid gland since it is relatively low-cost and safety. Fine needle aspiration biopsy (FNAB) is usually used by radiologists to determine the thyroid nodule whether malignant or benign. Commonly, malignancy of thyroid nodule determined based on shape feature. This research proposes a scheme for classifying...
This paper describes a method of grasp point detection from an item of cloth with unarranged shape. We focus on the combination of grasp point detector with shape classifier. In the proposed method, Convolutional Neural Network(CNN) is generated for shape classification, and it is also used for extracting a feature vector that presents shape characteristics. Using the feature, grasp points are calculated...
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