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Single feature extract method for image retrieval usually cannot get good results and it is hard to find a stable fusion method when across image datasets because the image descriptors usually describe image from single aspect. For this pragmatic issue, an improved FCTH-BoVW feature fusion algorithm called robust FCTH-BoVW is proposed in this paper. Traditional feature fusion methods almost use liner...
This paper presents a novel object extraction method using a micro air vehicle (MAV) for improving the robustness of occlusion. The proposed method is based on saliency of objects for extracting regions of interest (RoIs) using scale invariant feature transform (SIFT) features and segmentation of target objects using GrabCut, which requires advance learning. We obtained original aerial photographic...
In recent years, deep convolutional neural networks have achieved state of the art performance in various computer vision tasks such as classification, detection or segmentation. Due to their outstanding performance, CNNs are more and more used in the field of document image analysis as well. In this work, we present a CNN architecture that is trained with the recently proposed PHOC representation...
The H-KWS 2016, organized in the context of the ICFHR 2016 conference aims at setting up an evaluation framework for benchmarking handwritten keyword spotting (KWS) examining both the Query by Example (QbE) and the Query by String (QbS) approaches. Both KWS approaches were hosted into two different tracks, which in turn were split into two distinct challenges, namely, a segmentation-based and a segmentation-free...
Action classification in videos has been a very active field of research over the past years. Human action classification is a research field with application to various areas such as video indexing, surveillance, human-computer interfaces, among others. In this paper, we propose a strategy based on decreasing the number of features in order to improve accuracy in the human action classification task...
This paper presents superpixel-based background removal methods to increase accuracy of global salience person re-identication method. The current algorithm has two problems which limit its accuracy including (1) wrong matching when images of different people have the same background and/or (2) salience on the background of different images of different people is similar. Theoretical maximum accuracy...
Non-Photorealistic Rendering (NPR) for video sequences can be regarded as an extension of NPR for images. However, if the NPR sequence is obtained from a real video using an image processing pipeline, discontinuity problems have to be addressed, especially for the background region. In this paper, we propose to adopt Fast Video Segmentation algorithm to extract the common background in the video before...
Image retargeting methods change the size of images to an arbitrary resolution while protecting visually important regions from distortion. Since retargeting methods deform contents of an image based on these importance, importance calculation methods suitable for image retargeting is needed. In this paper, we propose a framework to improve an importance map by using depth and segmentation information...
Today, computer-based training is developing rapidly. The visual education is also quite commonly used in higher education as well as in primary and secondary education. The tablets, smart boards and computers constitute the basis of visual education. Visual education has many advantages, such as learning faster, memorability and in terms of paper expenses. The visual animations and presentations...
In this paper, we present methods for segmenting noisy two-dimensional forward-scan sonar images and classify and model their background. The segmentation approach differentiates the highlight blobs, cast shadows, and the background of sonar images. There is usually little information within relatively large background regions corresponding to the flat sea bottom and (or) water column, as they are...
Multi-agent technology has been considered as an important approach for developing distributed intelligent systems analyzing computed tomography (CT). Due to the important interactions, multi-agent problem complexity can rise rapidly with the number of agents or their behavior. We present a MAS solution that has spawned increasing interest in machine techniques to automate the search and optimization...
Web based Image search engine is a contrivance using that re-ranking of numerous images from web is possible as well as matching of images in semantic space for which attributes and reference classes are possible. Nowadays, with user search intention web search engine provide set of relevant as well as irrelevant Images to user and then user select query Image from pool and then remaining Images are...
In this paper, a new method of edge detection in gray scale images based on comparing a pixel's value to its eight neighbors' values is presented. Each pixel gets a new value based on such comparison. Similar pixels or smooth surfaces are then those which have a zero value resulting from the sum of all values and the edges are the set of pixels whose values are different from zero. This decision of...
The use of intrinsic motivation for the task of learning sensori-motor properties has received a lot of attention over the last few years, but only little work has been provided toward using intrinsic motivation for the task of learning visual signals. In this paper, we propose to apply the main ideas of the Intelligent Adaptive Curiosity (IAC) for the task of visual saliency learning. We here present...
Coronary Cine-angiogram (CCA) is one of the widely used preliminary invasive medical image modalities in Interventional Cardiology for the detection of luminal obstructions in Coronary Artery (CA) vasculature. It is apparent that the clinical judgments based on angiography are subjective and lead to overestimation and underestimation of the detected stenosis. Hence, such imprecise diagnosis can have...
In this paper, a 3D image watermarking scheme is proposed to embed the watermark with the depth of the 3D image for depth image based rendering (DIBR) 3D image representation. To make the scheme invariant to view synthesis process, watermark is inserted with the scale invariant feature transform (SIFT) feature point locations obtained from the original image. Moreover, embedding zone for watermarking...
Text detection is typically the first step for any text processing such as hand-written text recognition, layout analysis, line detection, or writer identification. This paper describes a new method to detect text in images, particularly in historical document images. For a robust detection, we propose the use of the vesselness filter as a new preprocessing step for text detection. We show, that this...
We develop an unsupervised graph clustering and image segmentation algorithm based on non-negative matrix factorization. We consider arbitrarily represented visual signals (in 2D or 3D) and use a graph embedding approach for image or point cloud segmentation. We extend a Projective Non-negative Matrix Factorization variant to include local spatial relationships over the image graph. By using properly...
In this paper we introduce a novel method for general semantic segmentation that can benefit from general semantics of Convolutional Neural Network (CNN). Our segmentation proposes visually and semantically coherent image segments. We use binary encoding of CNN features to overcome the difficulty of the clustering on the high-dimensional CNN feature space. These binary codes are very robust against...
High dynamic range imaging is currently being introduced to television, cinema and computer games. While it has been found that a fixed encoding for high dynamic range imagery needs at least 11 to 12 bits of tonal resolution, current mainstream image transmission interfaces, codecs and file formats are limited to 10 bits. To be able to use current generation imaging pipelines, this paper presents...
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