Abstract
In the present thesis the author undertakes the problem of the objects selecting on pictures. The novel conception of using depth map as a base to objects marking was proposed here. objects separation can be done on the base of depth (disparity), corresponding to points that should be marked. This allows for elimination of textures, occurring in background and also on objects. The object selection process must be preceded by picture’s depth analysis. This can be done by the novel neural structure: Self-Correcting Neural Network. This structure is working point-by-point with no picture’s segmentation before.
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Laskowski, L.: A Novel Self-Correcting Neural Network in the Objects Selection Task (publication under redaction)
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Laskowski, Ł. (2012). Objects Auto-selection from Stereo-Images Realised by Self-Correcting Neural Network. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_14
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DOI: https://doi.org/10.1007/978-3-642-29347-4_14
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