Craters, ridges and rocks are the features to be extracted in the lunar images. Proposed methodology deals with detection of linear feature such as (i) ridges, (ii) lineaments and (iii) nonlinear features like craters. All edges are identified as either crater or lineament. Therefore, all circular edges are recognized as craters edges, and those remained edges, which are not crater edges and low possibility of the noise, are recognized as lineaments in the remained edges. The Steps for lineament recognition includes the steps such as Crater Rim Elimination, Small Area Elimination and Lineament Classification. Ridges detection includes edge extraction using haar wavelet transform followed by morphological operations such as dilation and erosion. For detection of non linear features such as craters, the most predominant feature on the lunar terrain, circular hough transform is used. But it fails to detect craters without proper connected edges because of presence of shadows in an image. This paper includes algorithms for shadow removal in the images which accounts for changes in illumination, visual appearance, and size. Results indicate that the detection rate is improved with shadow removal techniques. KEYWORDS Feature extraction, Shadow removal, linear feature, non linear feature, Ridges, Circular hough transform.
CITATION STYLE
Tamililakkiya, V. (2011). Linear and Non-Linear Feature Extraction Algorithms for Lunar Images. Signal & Image Processing : An International Journal, 2(4), 161–172. https://doi.org/10.5121/sipij.2011.2414
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