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 the image retrieval, “Fusion” refers to the problem where two or more ranked image lists are merged into a single ranked list and the unified list is presented to the user. In this paper, we focus on the combination of two ranked results from the independent Short term learning methods with Reciprocal Rank Fusion to improve the accuracy of the system. To evaluate the proposed method, we implement...
Skin detection is the preliminary stage of many computer vision applications. In this paper, a statistical fusion model is proposed for detecting skin regions in arbitrary images. We used conditional random field (CRF) to statistically combine the information of different color spaces and model the spatial relationship between image pixels. The conditional probability distribution of labels (skin...
This research represents a method to detect malaria parasite in blood samples stained with giemsa. In order to increase the accuracy of detecting, at the first step, the red blood cell mask is extracted. It is due to the fact that most of malaria parasites exist in red blood cells. Then, stained elements of blood such as red blood cells, parasites and white blood cells are extracted. At the next step,...
Image retrieval tools can assist people in making efficient use of digital image collections; also it has become imperative to find efficient methods for the retrieval of these images. Most image processing algorithms are inherently parallel, so multithreading processors are suitable in such applications. In very big image databases, image processing takes very long time for run on a single core processor...
Identification of minerals in petrographic thin sections using intelligent methods is very complex and challenging task which, mineralogists and computer scientists are faced with it. Textural features have very important role to identify minerals, and undoubtedly without using these features, recognition minerals in thin sections yield to many miss classification results. Thin sections have been...
In this paper, we present an interactive algorithm to separate foreground and background regions of natural images (natural image matting) using ant colony optimization. Today, image matting is one of the most challenging and interesting research fields in image processing. In our approach instead of preparing a trimap, the user specifies foreground and background regions by some red and blue scribbles...
This paper presents a color image classification method using rank based ensemble classifier. In this paper, we use color histogram in different color spaces and Gabor wavelet to extract color and texture features respectively. These features are classified by two classifiers: Nearest Neighbor (NN) and Multi Layer Perceptron (MLP). In the proposed approach, each set of features are classified by each...
Texture classification is an important part of many object recognition algorithms. In this paper, a new approach to texture classification is proposed. Recently, local binary pattern (LBP) has been widely used in texture classification. In conventional LBP, directional statistical features and color information are not considered. To extract color information of textures, we have used color LBP. Also,...
Soccer video processing and analysis to find critical events such as occurrences of goal event have been one of the important issues and topics of active researches in recent years. In this paper, a new role-based framework is proposed for goal event detection in which the semantic structure of soccer game is used. Usually after a goal scene, the audiences' and reporters' sound intensity is increased,...
Tracking failure is an inevitable problem in any object tracking algorithm. Online evaluation of a tracking algorithm to detect and correct failures is therefore an important task in any object tracking system. In this paper we propose an early tracking failure detection procedure for the Continuously Adaptive Mean-Shift(CAMShift) tracking algorithm. We also propose an algorithm to modify the tracker...
In this paper, a semantic segmentation method for aerial images is presented. Semantic segmentation allows the task of segmentation and classification to be performed simultaneously in a single efficient step. This algorithm relies on descriptors of color and texture. In the training phase, we first manually extract homogenous areas and label each area semantically. Then color and texture descriptors...
Tracking objects using Mean Shift algorithm fails when there is a full/partial occlusion or when the background color and the desired object are close. In this paper we proposed a method using Kalman Filter and Mean Shift for handling these situations. Using similarity measure of Mean Shift algorithm we are able to detect an occlusion. Kalman Filter comes into the play for occlusion handling in a...
During the last decades a large set of video archives is created and rapidly multimedia growth creates new challenge in the image processing world. A reliable system is needed to automate the process of this large amount of data. Video analyses are done in two different levels, low level and high level. There are many problems in video content analysis and in this work we analyzed content based video...
Image and video processing techniques are one of the commonly used methods for traffics monitoring. This paper investigates the image processing techniques based vehicles speed measurement issue using only a fixed single camera. Therefore, a geometrical calculation based method is proposed. Based on this method, first a moving vehicle is detected in a video background and then the vehicle speed is...
Human action recognition is the process of labeling videos contain human motion with action classes. The run time complexity is one of the most important challenges in action recognition. In this paper, we address this problem using video abstraction techniques including key-frame extraction and video skimming. At first we extract key-frames and then skim the video clip by concatenating excerpts around...
In this paper we describe designing and implementation of a powerful, fast and compact simple 3D modeler (SM3D). In addition to saving cost and time (due to high processing speed), 3D objects can be created with minimum system resources by using this application. Easy learning and using are other strengths of this application. Modularity using classification and applying Dynamic-Link Library files...
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.