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Spectral classification for hyperspectral image is a challenging job because of the number of spectral in a hyperspectral image and high dimensional spectral. In this paper, we proposed a method to enhance the spectral classification using the Adaboost for hyperspectral image analysis. By applying the Adaboost algorithm to the classifier, the classification can be executed iteratively by giving weight...
This paper present a new feature extractors called the Fractionalized Principle Magnitude (FPM) that is evaluated in the classification of approved Halal logo with respect to classification accuracy and time consumptions. Feature can be classified into two group; global feature and local feature. In this study, several feature extractors have been compared with the proposed method such as histogram...
This paper proposes a novel descriptor, referred to as the localized angular phase (LAP), which is robust to illumination, scaling, and image blurring. LAP utilizes the phase information from the Fourier transform of the pixels in localized polar space with a fixed radius. The application examples of LAP are presented in terms of content-based image retrieval, classification, and feature extraction...
Rotation invariant texture descriptor plays an important role in texture-based object classification. However the classification accuracy may decrease due to the inconsistent performance of texture descriptor with respect to various rotated angles. In this paper we propose a consistent rotation invariant texture descriptor named Sorted Neighborhood Differences (SND). SND is derived from the integration...
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