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, a 3D reconstruction algorithm using CT slices of human pelvis is presented. We propose the method for 3D image reconstruction that is based on a combination of the SURF (Speeded-Up Robust Features) descriptor and SSD (Sum of Squared Differences) matching algorithm using image segmentation with aim to obtain accurate 3D model of human pelvis. Firstly, we apply image filtering for noise...
In this paper, a novel system for automatic detection and classification of animal is presented. System called ASFAR (Automatic System For Animal Recognition) is based on distributed so-called ‘watching device’ in designated area and main computing unit (MCU) acting as server and system manager. Watching devices are situated in wild nature and their task is to detect animal and then send data to MCU...
Nowadays, health application has growing market potential. In this paper, an investigation of electro-conductive, parameters of blended silver coated polyamide yarn were measured. We focused on the several objectives important in electro-conductive yarns design and application into intelligent clothing. In detail, the effect of numbers of silver filaments, draft and twists, the effect of external...
This paper deals with research in area of automatic semantic inclusion of textual and non-textual information of Web documents. The main idea is to create a robust method for extraction of images and textual segments to obtain short web document. Thus, developed method consist of two data types extractions, where both, image and text data extraction are using Document Object Model (DOM) tree. Extracted...
This paper provides a new feature extraction method for object recognition using PCA-KNN algorithm with SIFT descriptor. The proposed method is divided into three steps. The first step is based on feature extraction from the input images using SIFT (Scale Invariant Feature Transform) descriptor. Each of the features is represented using one or more feature descriptors. In medical systems images used...
This paper deals with research in the area of automatic extraction of textual and non-textual information and their classification. The main idea is to create a robust method for extraction of image and textual segments to obtain short web document. Thus, developed method consist of two data types extractions, where both image and text data extraction are using Document Object Model tree. Extracted...
This paper provides an example of the face recognition using SIFT-PCA method and impact of Graph Based segmentation algorithm on recognition rate. Principle component analysis (PCA) is a multivariate technique that analyzes a face data in which observation are described by several inter-correlated dependent variables. The goal is to extract the important information from the face data, to represent...
This paper deals with research in the area of image analysis. Our approach is based on hybrid segmentation and Scale-Invariant Feature Transform (SIFT) method. The main idea is to improve the process of object recognition and their classification into classes by Support Vector Machine (SVM) classifier. The fast and powerful hybrid segmentation algorithm based on Mean Shift and Believe Propagation...
The texture feature extraction plays important role in image analysis. This paper deals with improvement of the one-dimensional version of GLCM (Gray Level Cooccurrence Matrix). In our approach, the color information of texture was taken into consideration. The novel One dimensional Color Level Co-occurrence Matrix (1D-CLCM) are designed. Performances of proposed method are verified on database of...
In the image analysis, image segmentation is the operation that divides image into set of different segments. The paper deals about common color image segmentation techniques and methods. The advantages and disadvantage of each one will be described in this paper. At the end of the paper, the evaluation criterion will be introduced and applied on the algorithms results. Five most used image segmentation...
This paper provides an example of the face recognition using PCA method and impact of segmentation algorithm ‘Belief Propagation’ on recognition rate. Principle component analysis (PCA) is a multivariate technique that analyzes a face data in which observation are described by several inter-correlated dependent variables. The goal is to extract the important information from the face data, to represent...
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.