Detection and Classification of Local Primitives in Line Drawings
نویسندگان
چکیده
The local primitives found in binary images are useful in the analysis and recognition of document and patent images. In this paper, an optimum detection of end points and junction points is obtained using morphological spurring and the granulometric curve of the image. A distance based algorithm is proposed to classify the local primitives found at the detected points. The size of the local region to classify a local primitive is determined granulometrically using the average thickness of lines found in the image. The classified primitives are quantized using a variant of local binary patterns. Ground truth is created and an analysis of the classification accuracy is performed. The values for all the parameters used in the proposed method are determined granulometrically which makes it scale invariant.
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