Open Journal Systems

Automatic Contextual Thresholding of Color Images: Application in Road Seed Extraction

Giovane Maia do Vale, Rodrigo Bruno Zanin, Aluir Porfírio Dal Poz


In this paper is a totally automatic strategy proposed to reduce the complexity of patterns (vegetation, building, soils etc.) that interact with the object ´road´ in color images, thus reducing the difficulty of the automatic extraction of this object. The proposed methodology consists of three sequential steps. In the first step the punctual operator is applied for artificiality index computation
known as NandA (Natural and Artificial). The result is an image whose the intensity attribute is the NandA response. The second step consists in automatically thresholding the image obtained in the previous step, resulting in a binary image. This image usually allows the separation between artificial and natural objects. The third step consists in applying a preexisting road seed extraction methodology to the previous generated binary image. Several
experiments carried out with real images made the verification of the potential of the proposed methodology possible. The comparison of the obtained result to others obtained by a similar methodology for road seed extraction from gray level images, showed that the main benefit was the drastic reduction of the computational effort.


Limiarização; Extração de Rodovias; Imagens Coloridas; Índice de Artificialidade; Thresholding; Road Extraction; Color Image; Artificiality Index