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The paper presents the algorithm for text line segmentation based on the oriented anisotropic Gaussian kernel. Initially, the document image is split into connected components achieved by bounding boxes. These connected components are cleared from redundant fragments. Furthermore, the binary moments are applied to each of these connected components evaluating local text skewing. According to this information the orientation of the anisotropic Gaussian kernel is set. After the algorithm application the boundary growing areas around connected components are established. These areas are of major importance for the evaluation of text line segmentation. For testing purposes, the algorithm is evaluated under different text samples. Comparative analysis between algorithm with and without orientation based on the anisotropic Gaussian kernel is made. The results show the improvement in the domain of text line segmentation.

–917. [24] D. Brodić, “Text Line Segmentation with Water Flow Algorithm based on Power Function”, Journal of Electrical Engineering vol. 66, no. 3, 2015, pp. 132–141. [25] D. Brodić and Z. N. Milivojević, “Text Line Segmentation with the Algorithm based on the Oriented Anisotropic Gaussian Kernel”, Journal of Electrical Engineering vol. 64, no. 4, 2013, pp. 238–24.

historical handwritten documents. IEEE Transactions on Pattern Analysis and Machine Intelligence , 27 (8), 1212-1225. Brodić, D., Milivojević, Z. (2010). Optimization of the Gaussian kernel extended by binary morphology for text line segmentation. Radioengineering , 19 (4), 718-724. Razak, Z., Zulkiflee, K., et al. (2008). Off-Line handwriting text line segmentation: a review. International Journal of Computer Science and Network Security , 8, 12-20. Brodić, D. (2010). Optimization of the anisotropic Gaussian kernel for text segmentation and parameter extraction. In