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This paper proposes an approach for structure based separation of image objects using fuzzy morphology for aerial images. With set operators in fuzzy context, we apply an adaptive alpha-cut morphological processing for edge detection and image enhancement. A Top-hat transform is first applied to the input image and the resulting image is thresholded to a binary form. The image is then thinned using hit-or-miss transform. Finally, m-connectivity is used to keep the desired number of connected pixels. The output image is overlaid on the original for enhanced boundaries. Experiments were performed on a variety of aerial images. A comparison to other edge enhancement techniques like and filtering shows improved performance by the proposed technique. Refereed/Peer-reviewed

This paper presents a novel algorithm based on Fuzzy Morphology for the computer-assisted enhancement of exudates in fundus images of human retina for the diagnosis of diabetic retinopathy. Diabetic retinopathy is a common disease in diabetic persons. The disease is diagnosed by the presence of exudates in the macular region. Here, we use Fuzzy Morphology for the enhancement of exudates. The fundus image is first converted to gray scale followed by a series of fuzzy erosion and fuzzy dilation (morphological closing operation) with a diamond shaped structuring element. Finally, the resulting image is added to the original image to transform into enhanced one. Experiments were performed on a database of variety of fundus images with and without the disease. The experiments led to convincing results and the images were enhanced for easier clinical examination. Refereed/Peer-reviewed