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In this letter, we propose to use an enhanced version of volumetric directional pattern to efficiently extract rich spatial context information in the hyperspectral imagery (HSI). The proposed technique fuses the texture information from three consecutive bands in the input HSI. The extracted local image texture features for each pixel of interest are then fed into an extreme learning machine classifier...
Sparse representation based classification (SRC) has been introduced as a new algorithm for face recognition classification instead of the classical gradient-based algorithms. However, there are some limitations that influence the robustness properties in SRC. One of the most effective parameters that impacts the SRC performance is the directory of training samples. It should contain enough samples...
Accurate and efficient object tracking is an important aspect of various security and surveillance applications. In object tracking solutions which utilize intensity-based histogram feature methods for use on wide area motion imagery (WAMI), there currently exists tracking challenges due to object structural information distortions and pavement/background variations. The inclusion of structural target...
In this paper, we present a new framework for building change detection from monocular aerial imagery that automatically predicts building candidates based on adaptive local textural features with successive background removal. An adaptive local entropy feature is developed based on quadratic regression and Random Sample Consensus (RANSAC) for extracting potential building candidates. Then a majority...
This paper presents an illumination invariant face recognition system that uses local directional pattern descriptor and modular histogram. The proposed Modular Histogram of Oriented Directional Features (MHODF) is an oriented local descriptor that is able to encode various patterns of face images under different lighting conditions. It employs the edge response values in different directions to encode...
We present an automated mechanism that can detect and characterize the building changes by analyzing airborne or satellite imagery. The proposed framework can be categorized into three stages: building detection, boundary extraction and change identification. To detect the buildings, we utilize local phase and local amplitude from monogenic signal to extract building features for addressing issues...
This paper presents an efficient preprocessing algorithm for big data analysis. Our proposed key-frame selection method utilizes the statistical differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames. We anticipate that such key frame selection technique will have significant impact...
We present an automated mechanism that can detect and issue warnings of machinery threat such as the presence of construction vehicles on pipeline right-of-way. The proposed scheme models the human visual perception concepts to extract fine details of objects by utilizing the corners and gradient histogram information in pyramid levels. Two real-world aerial image datasets are used for testing and...
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