Paravecino, Fanny N.

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    Object recognition using spherical harmonics shape descriptor in hyperspectral imagery
    (2011) Paravecino, Fanny N.; Manian, Vidya; College of Engineering; Velez-Reyes, Miguel; Seguel, Jaime; Department of Electrical and Computer Engineering; Romero, Juan
    Object recognition in hyperspectral and multispectral imagery has been studied in the last decade. The different approaches to recognition over hyperspectral images are based on spectral behavior, ignoring the shape behavior. On the other hand in multispectral, RGB and gray scale images the approaches are many; mainly considering the shape of the object, but neither of them considering the spectral behavior. In this research, our focus is to develop an algorithm that recognize a man-made objects such cars, buildings, etc using their shape and corresponding spectral information, therefore a fusion of these two sets of information gives is exploited here. The algorithm starts by segmenting the object, to isolate it from the background and other objects, then determining its geometric center, so as to extract its boundary, the geometric center is important in order to extract the shape descriptor. For the shape descriptor we use spherical harmonics, this descriptor have been widely used as a powerful tool for shape recognition but has not been applied to hyperspectral imagery. Once we have the shape descriptor, the boundary of the object’s shape is analyzed and used to recognize it. The algorithm is tested using real hyperspectral images taken from HYDICE sensor, SOC 700 Hyperspectral camera and multispectral aerial images.