Triangular fuzzy interpolation deinterlacing algorithm method for image edge detection
by G.K. Jagatheswari; R. Murugesan
International Journal of Fuzzy Computation and Modelling (IJFCM), Vol. 4, No. 1, 2022

Abstract: Edge detection is the first step in image as it can be applied in the process of feature extraction, segmentation and classification. This study proposes a new fuzzy logic based edge detection method and computationally efficient algorithm based on triangular fuzzy interpolation technique for intra field deinterlacing of images that reduces the loss in image quality at the edges. The proposed algorithm improves image deinterlacing quality with respect to missing pixels in the edge region. When interpolating the missing pixels, characteristics or features of the region around the pixel are interpolated first. The proposed algorithm is tested with five test images which have both uniform surface and edges. The subjective and objective performance of the proposed algorithm shows greater improvement in the edge quality when correlated with the traditional deinterlacing methods. The designed fuzzy rules become an attractive solution for the betterment of the quality of edges as much as possible. The result reveals that the proposed algorithm provides greater robustness to contrast and lighting variations.

Online publication date: Mon, 25-Jul-2022

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