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Multimedia data is expanding exponentially. The rapid growth of technology combined with affordable storage and capabilities has lead to explosion in the availability and applications of multimedia. Most of the data is available in the form of images and videos. Today large amount of image data is produced through digital cameras, mobile phones and other sources. Processing of this large collection...
Object motion tracking has been done for videos with various methodologies. The existing systems are mainly based on single feature and motion detection as a single object by taking the movement of the feature selected. We propose a moving object tracking method that uses low-level features like centroid location of tracked object combined with the color feature. Centroid location of each moving object...
Major developments in image capture and image editing technologies have resulted in enormous increase of near duplicate data generation. This coupled with increased use of internet and availability of storage has led to large databases of such images being available. Hence, near-duplicate image detection and retrieval is an essential operation to refine image search results for effective user investigation...
As an efficient pre-processing technology, superpixel has been widely used in image segmentation, which improves the final results and reduces the complexity of the subsequent processing tasks. This paper presents an interactive image segmentation method based on the hierarchical superpixels initialization and region merging. It firstly proposes a novel hierarchical superpixels initialization framework...
This paper proposes a novel algorithm for Content Based Scene Retrieval (CBSR) using video features such as moment, histogram, Edge Histogram Descriptor (EHD)… This application is similar for Content Based Image Retrieval (CBIR) but instead of finding corresponding images in the database, it identifies the corresponding scene which contains the testing frame. The proposed algorithm can deal with scene...
In this paper, we present an approach for effective content based image retrieval by color and texture based on genetic algorithm and euclidean distance method to achieve good image retrieval performance in Android mobile environment. In recent years the Google's Android play an important role in mobile operating system. It can provide number of application to the user like e-mail, web browser, video...
User-generated images are now prevalent across social media platforms, such as Facebook, Twitter, and various blogospheres. These images can be categorized and ranked based on their relevant topics. In this paper, we present and compare candidate schemes for mining salient images related to a specific topic or object among a large number of images from a blogosphere. Identifying salient images consists...
In this paper, we propose an approach for object recognition using binary local invariant features and color information. In our approach, we use a fast detector for key point detection and binary local features descriptor for key point description. For local feature matching, the Fast library for Approximated Nearest Neighbors (FLANN) is applied to match the query image and reference image in data...
Region duplication is a common method to produce forgery images, where part of an image is copied and pasted somewhere else in the same image. In order to fit the scene better and leave no visible artifacts, the copied region may be processed by affine transforms before being pasted. Most of the existing methods cannot handle these transforms. This paper presents a method to detect the region-duplication...
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...
In this paper, we have developed a novel algorithm for book image retrieval that can find test book images accurately and efficiently. In our proposed algorithm, SIFT Vocabulary tree is first used to model the local information and to get the preliminary results. The final result is determined via multi-features joint decision. The multi-features are SIFT density, SIFT distribution histogram, edge...
The aim of this study is to develop a method of lesion extraction from a large image of a skin surface and evaluate a new set of color features and their ability to classify the extracted skin lesions‥ It is beneficial for a dermatologist to be able to take a snapshot of a large skin surface and have an automated system locate and diagnose atypical lesions. The proposed system accomplishes this task...
Background subtraction method is a tracking method only based on motion information. It cannot make a distinction between the foreground objects detected. The feature-based tracking methods need to select the appropriate prediction and search algorithm. But the algorithm complexity and amount of computation is large for the multi-target tracking. Therefore, this paper presents the method based on...
Object localization is a critical factor in automatic system testing, which poses two main difficulties: 1) the scale variation of the icons, 2) the absence of the gradient information in some icons. This paper proposes a systematic method based on cascade template matching to localize the object. Firstly we use the multiple templates of different scales to detect the object. Secondly we distinguish...
This paper proposes a Takagi-Sugeno (TS) fuzzy system learned through a support vector machine (SVM) in principal component space (TFS-SVMPC) for real-time object detection. The antecedent part of the TFS-SVMPC classifier is generated using an algorithm that is similar to fuzzy clustering. The dimension of the free parameter vector in the TS consequent part of the TFS-SVMPC is first reduced by principal...
Region-based image retrieval system has been an active research topic in areas such as, entertainment, education, multimedia, image classification and searching. The system decomposes an image into discrete regions and each region is described using primitive features such as color, texture, shape or the combination of them. The extracted regions are indexed and retrieved. One of the key issues with...
Multiple objects tracking is a challenging task. This article presents an algorithm which can detect and track multiple objects, and update target model automatically. The contributions of this paper as follow: Firstly, we use color histogram(HC) and histogram of orientated gradients(HOG) to represent the objects, model update is realized under the frame of kalman filter and gaussian model, secondly...
We propose an efficient image retrieval scheme to retrieve images. We extract the color pixel features by the HSV color space. The proposed scheme transfers each image to a quantized color code using the regulations of the properties in compliance with HSV model. Subsequently, using the quantized color code to compare the images of database. We succeed in transferring the image retrieval problem to...
This paper adds sift matching features into the particle filter tracking framework based on color histogram feature, and proposes a dual character tracking algorithm, in which the particle weights are calculated considering both the sift matching features and the color histogram feature. Experimental results show that the algorithm can effectively solve the problem of accumulating errors when inappropriately...
The ads exposure frequency in a TV is very important for the pricing of the advertising. If we count this exposure frequency by person, it will be very time consuming and error-prone. In this paper, we propose an approach and design a system for searching and counting the number of banner ads appearing in sports videos. The searching proceeds by matching feature points from pre-specified sample ads...
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