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This paper proposes a hierachical method for traffic sign detection by employing extreme learning machine (ELM) whose infrastructure is a single-hidden-layer feedforward network. This proposed method consists of three modules: Coarse detection module, fine detection module and candidates clustering module. Histogram of oriented gradient (HOG) and color histogram are used as features of signs. This...
Nowadays, content-based image-retrieval techniques constitute powerful tools for archiving and mining of large remote sensing image databases. However, the gap between low-level unsupervised extracted features in content-based retrieval and the high-level semantic concepts of user queries limits their performances. For that reason, we propose an adaptive content based image retrieval (CBIR) approach...
3D object recognition is a fundamental research topic. However, shape only feature descriptors for 3D object recognition have been the main focus of research. With the availability of low cost range plus color sensors, color based descriptors have attracted increasing attention lately. In this paper we present novel 3D object recognition algorithms which use not only shape but also color cues. We...
The aim of this paper is to increase the success rate of CBIR system with low computational complexity. The success rate of CBIR system depends on localization of the image to be retrieved. This can be achieved by using textons of R, G, B planes of the image which describes the shape. This paper proposes 3 × 3 grids to extract the textons with low computational complexity. The proposed method is based...
Single-feature-based image retrieval system of content-based video retrieval system has a lower performance. In this paper, a algorithm of image retrieval based on NMI invariable feature of dominant color and texture feature is proposed. The shape information and the spatial distribution of dominant color can be described by the NMI invariable feature of dominant color. so the content feature of image...
An algorithm for fast shot boundary detection based on SVM (Support Vector Machine) is proposed. In this algorithm, smooth intervals inside shots are first eliminated from the original video frame sequence. During this process, a gray variance sequence is extracted and serves as the basis for the detection of smooth intervals. Then a new frame sequence named RFS (Reordered Frame Sequence) is formed...
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