Topic
Structuring element
About: Structuring element is a research topic. Over the lifetime, 997 publications have been published within this topic receiving 26839 citations.
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19 Sep 2017
TL;DR: Connective morphology has been an active area of research for more than two decades as mentioned in this paper and the progress in this field has been threefold: development of a mathematical framework, development of fast algorithms, and application of the methodology in very diverse fields.
Abstract: Connective morphology has been an active area of research for more than two decades. Based on an abstract notion of connectivity, it allows development of perceptual grouping of pixels using different connectivity classes. Images are processed based on these perceptual groups, rather than some rigid neighbourhood imposed upon the image in the form of a fixed structuring element. The progress in this field has been threefold: (i) development of a mathematical framework; (ii) development of fast algorithms, and (iii) application of the methodology in very diverse fields. In this talk I will review these developments, and describe relationships to other image-adaptive methods. I will also discuss the opportunities for use in multi-scale analysis and inclusion of machine learning within connected filters.
20 Oct 2004
TL;DR: The comparison results demonstrate that the proposed approach can differentiate texture images more effectively and provide more robust segmentation results.
Abstract: This paper deals with the problem of segmenting various textures. For this purpose, we have applied mathematical morphology for the multifractal analysis of images. The digital gray level image is treated as a 3D surface whose multifractal measures are calculated by performing dilations on this surface. Plotting the acquired measures against the size of the structuring element, the local morphological multifractal exponents can be estimated, based on which the unsupervised fuzzy C-means clustering method is used to segment a texture image into the desired number of classes. Randomly choosing 12 natural textures from the Brodatz album, 66 mosaics of 2 textures and 495 mosaics of 4 textures are used to test the new segmentation approach and other two techniques, where the multifractal features are extracted by the box-counting based methods. The comparison results demonstrate that the proposed approach can differentiate texture images more effectively and provide more robust segmentation results.
01 Jan 2022
TL;DR: In this paper , a representation of scores similar to piano rolls that use chromas instead of pitches is proposed, and a group structure to the Time-Frequency plane is used to analyze two Chopin's Nocturnes.
Abstract: Mathematical Morphology provides powerful tools for image processing, analysis and understanding. In this paper, we apply these tools to analyze scores, that are image-like representations of Music. To do that, we consider chroma rolls, a representation of scores similar to piano rolls that use chromas instead of pitches. Endowing this representation with a lattice structure, one can define Mathematical Morphology operators, and setting a group structure to the Time-Frequency plane allows us to use the notion of structuring element. We show throughout some examples that this relates with the notion of pitch-class set and chord progressions, and we analyze two Chopin’s Nocturnes with this technique.
08 Oct 2022
TL;DR: In this paper , a new Optic Disc segmentation mechanism based on Composite Filtering and Mathematical Morphology has been proposed, which is accomplished under twofold; they are (1) OptIC Disc Pixel (ODP) identification and (2) OPTIC Disc Segmentation.
Abstract: Optic Disc is one of the important attributes which signifies the status of Different eye related diseases like Diabetic Retinopathy, Glaucoma etc. For this purpose, accurate segmentation of Optic Disc from retinal images is essential. Towards such prospect, this paper proposes a new Optic Disc segmentation mechanism based on Composite Filtering and Mathematical Morphology. The complete methodology is accomplished under two-fold; they are (1) Optic Disc Pixel (ODP) identification and (2) Optic Disc Segmentation. In the first fold, ODP is located as an average of candidate pixel locations which are obtained through three different filters namely Median, Gaussian and Variance filters. Next, the final Optic Disc is segmented after the removal of blood vessels with the help of Linear and Rotational Structuring element. For experimental validation, two standard datasets namely DRIVE and MESSIDOR are used, and the performance is measured through Accuracy, sensitivity, specificity and overlap score. The average sensitivity, specificity and overlap score of proposed method is observed as 0.8865, 0.8722, and 0.8472 respectively. Further, the average improvement in the accuracy gained by proposed method is observed as 5.31%.
01 Jan 2013
TL;DR: Considering the edge ringing effect is not only relevant to the edge pixels, but also relevant to their neighboring pixels, the method dilate the edge-detected image with a structuring element so as to obtain thicker image edges.
Abstract: Projections onto convex sets (POCS) algorithm is a widely used super-resolution image reconstruction method. Aiming at the edge ringing effect of traditional POCS algorithm, this paper analyzes the basic reason causing the effect, and adopts an improved POCS algorithm to reduce it. In the improved algorithm, the Point Spread Function (PSF) centered at any edge pixel is weighted, making the far the position of the PSF coefficient is from the edge, the smaller the corresponding PSF coefficient is, and the coefficients remain unchanged along the edge direction. This paper uses wavelet transform modulus maxima method to detect image edges. Considering the edge ringing effect is not only relevant to the edge pixels, but also relevant to their neighboring pixels, we dilate the edge-detected image with a structuring element so as to obtain thicker image edges. Experimental results show that our method greatly reduces the edge ringing effect at little cost in terms of image sharpness, so we can get a better reconstruction image.