The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, the automatic segmentation of Osteosar-coma in MRI images is formed as a clustering problem. Subsequently, a new dynamic clustering algorithm based on the Harmony Search (HS) hybridized with Fuzzy C-means (FCM) called DCHS is proposed to automatically segment the Osteosarcoma MRI images in an intelligent manner. The concept of variable length in each harmony memory vector is applied...
This paper presents a new automatic initialization procedure for a level-set based segmentation algorithm that works on all slices for a given CT dataset. Level set segmentation algorithms provide promising results, are robust to dataset variations and do not require prior training. As such, they can be reliably used for segmentation of major organs in abdominal CT scans. However, level set algorithms...
In this paper, a new dynamic clustering approach based on the harmony search algorithm (HS) called DCHS is proposed. In this algorithm, the capability of standard HS is modified to automatically evolve the appropriate number of clusters as well as the locations of cluster centers. By incorporating the concept of variable length in each harmony memory vector, DCHS is able to encode variable numbers...
In this paper, we propose an approach to learn the kernel which uses transferred knowledge from unlabeled data to cope with situations where training examples are scarce. In our approach, unlabeled data has been used to construct an optimized kernel that better generalizes on the target dataset. For the proposed kernel learning algorithm, Fisher Discriminant Analysis (FDA) is used in conjunction with...
Image segmentation is considered as one of the crucial steps in image analysis process and it is the most challenging task. Image segmentation can be modeled as a clustering problem. Therefore, clustering algorithms have been applied successfully in image segmentation problems. Fuzzy c-mean (FCM) algorithm is considered as one of the most popular clustering algorithm. Even that, FCM can generate a...
We propose a new approach to tackle the well known fuzzy c-means (FCM) initialization problem. Our approach uses a metaheuristic search method called Harmony Search (HS) algorithm to produce near-optimal initial cluster centers for the FCM algorithm. We then demonstrate the effectiveness of our approach in a MRI segmentation problem. In order to dramatically reduce the computation time to find near-optimal...
Domain-specific ontologies encode reusable domain vocabulary and represent established domain semantics. The alignment of such ontologies requires an approach based on a semantic analysis of its components. This paper presents SLADO, Semantic Lexical Alignment for Domain-specific Ontologies. The proposed approach aims to use the available dictionaries and lexical resources in the underlying domain...
Image processing plays an important role in computer science, making complex image manipulation more feasible. It can be used either in a general manner or in specific domains such as for medical purposes. With the availability of the internet, image processing applications can be distributed to be available for different people, regardless of their geographical location. Although there are a handful...
Ribonucleic acid (RNA) has important structural and functional roles in the cell and plays roles in many stages of protein synthesis. The structure of RNA largely determines its function. Current physical methods for structure determination are time-consuming and expensive, thus the methods for the computational prediction of structure are necessary. Various algorithms that have been used for RNA...
This paper presents a new segmentation method that integrates a wavelet based feature, which is able to enhance the dissimilarity between regions with low variations in intensity. This feature is integrated to formulate a new level set based active contour model that addresses the segmentation of regions with highly similar intensities in medical images, which do not have clear boundaries between...
One major challenge faced by segmentation techniques in analyzing and visualizing individual slices of a 3D anatomical structure, is the degree of manual interaction required. To alleviate this problem, researchers have proposed the automatic incorporation of anatomical knowledge, via medical atlases to assist with the segmentation process. Some solutions include constructing specialized simple 2D,...
In object class recognition, lots of past researches focused on the local descriptors such as SIFT to categorize the variation of objects belonging to the same category in different poses, sizes, and appearance. However, SIFT descriptors may produce poor result especially if the object does not have enough information of its texture features. Due to this problem, we hypothesize that the use multi...
Overlaid text appears frequently in broadcast sports video. They provide supplementary information regarding the happenings of a particular game. Examples include important events of interest such as bookings and substitutions in a soccer match. Furthermore, overlaid-text is displayed when a particular concept of interest is happening or has happened. This paper presents a technique to automatically...
Current physical methods for RNA structure determination are time consuming and expensive; thus the methods for the computational prediction of structure are necessary. Various algorithms have been used for RNA structure prediction including dynamic programming and meta-heuristic algorithms. This paper proposes a meta-heuristic harmony search algorithm (HSRNAFold) for finding RNA secondary structure...
This paper presents a hybrid algorithm for object based clustering. The algorithm is designed based on hybrid of hierarchical and k-means clustering algorithm. For this work, we used dataset consist of natural imagery collected from PASCAL database 2006 collection and Google images. A collection of low level features image is used to validate the performance of our approach. Experimental results show...
Object class recognition is a highly challenging area in computer vision and machine learning. In this paper, we introduce a novel approach to object class recognition using Neuro Evolution of Augmenting Topologies (NEAT) to evolve artificial neural networks (ANN) capable of taking advantage of the robust SIFT feature based descriptor histograms. We claim that NEAT can produce ANN classifier which...
Overlaid-text appears frequently in broadcast sports video. They provide a plethora of information regarding the goings-on of a particular game. Examples include important events and video segments of interest such as bookings and half-time analysis, respectively. Furthermore, it is common that overlaid text is displayed when a particular concept is happening or has happened. This paper presents a...
This paper introduces Textured Renyi Entropy for image thresholding based on a novel combination mechanism. The Renyi Entropy is extended by modifying its priori, while still preserving overall functionality. An optional priori is introduced to improve accuracy. The priori modification allows adding of texture information in an efficient way, which results in more accurate thresholding. Furthermore,...
We present a simple technique to isolate and detect Cupriavidus sp. bacterium in microscopy images as a non-destructive means to monitor the growth and evolution of the bacteria. The approach uses OTSU binarization on the saturation channel of the bacteria sample images followed by morphological processing. This method of analysis has significantly speeded up the monitoring of biomass production from...
In this paper, a novel approach to automatically segment the optic disc contour using the center point of an optic disc candidate is proposed. The optic disc segmentation algorithm consists of 2 stages. The first stage involves the removal of blood vessels that obscure the optic disc. The blood vessel structures are detected using morphological operations. These detected structures are then removed...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.