| 1. |
- Bernander, Karl B., et al.
(författare)
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Improving the stochastic watershed
- 2013
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Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 34:9, s. 993-1000
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Tidskriftsartikel (refereegranskat)abstract
- The stochastic watershed is an unsupervised segmentation tool recently proposed by Angulo and Jeulin. By repeated application of the seeded watershed with randomly placed markers, a probability density function for object boundaries is created. In a second step, the algorithm then generates a meaningful segmentation of the image using this probability density function. The method performs best when the image contains regions of similar size, since it tends to break up larger regions and merge smaller ones. We propose two simple modifications that greatly improve the properties of the stochastic watershed: (1) add noise to the input image at every iteration, and (2) distribute the markers using a randomly placed grid. The noise strength is a new parameter to be set, but the output of the algorithm is not very sensitive to this value. In return, the output becomes less sensitive to the two parameters of the standard algorithm. The improved algorithm does not break up larger regions, effectively making the algorithm useful for a larger class of segmentation problems.
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| 2. |
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| 3. |
- Curic, Vladimir, et al.
(författare)
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Adaptive mathematical morphology – A survey of the field
- 2014
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Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 47, s. 18-28
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Tidskriftsartikel (refereegranskat)abstract
- We present an up-to-date survey on the topic of adaptive mathematical morphology. A broad review of research performed within the field is provided, as well as an in-depth summary of the theoretical advances within the field. Adaptivity can come in many different ways, based on different attributes, measures, and parameters. Similarities and differences between a few selected methods for adaptive structuring elements are considered, providing perspective on the consequences of different types of adaptivity. We also provide a brief analysis of perspectives and trends within the field, discussing possible directions for future studies.
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| 4. |
- Curic, Vladimir, et al.
(författare)
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Adaptive structuring elements based on salience distance transform
- 2012
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Ingår i: In Proceedings of Swedish Society for Image Analysis, SSBA 2012. - KTH, Stockholm.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Consequently they have good properties for filtering.
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| 5. |
- Ćurić, Vladimir, 1981-
(författare)
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Distance Functions and Their Use in Adaptive Mathematical Morphology
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One of the main problems in image analysis is a comparison of different shapes in images. It is often desirable to determine the extent to which one shape differs from another. This is usually a difficult task because shapes vary in size, length, contrast, texture, orientation, etc. Shapes can be described using sets of points, crisp of fuzzy. Hence, distance functions between sets have been used for comparing different shapes.Mathematical morphology is a non-linear theory related to the shape or morphology of features in the image, and morphological operators are defined by the interaction between an image and a small set called a structuring element. Although morphological operators have been extensively used to differentiate shapes by their size, it is not an easy task to differentiate shapes with respect to other features such as contrast or orientation. One approach for differentiation on these type of features is to use data-dependent structuring elements.In this thesis, we investigate the usefulness of various distance functions for: (i) shape registration and recognition; and (ii) construction of adaptive structuring elements and functions.We examine existing distance functions between sets, and propose a new one, called the Complement weighted sum of minimal distances, where the contribution of each point to the distance function is determined by the position of the point within the set. The usefulness of the new distance function is shown for different image registration and shape recognition problems. Furthermore, we extend the new distance function to fuzzy sets and show its applicability to classification of fuzzy objects.We propose two different types of adaptive structuring elements from the salience map of the edge strength: (i) the shape of a structuring element is predefined, and its size is determined from the salience map; (ii) the shape and size of a structuring element are dependent on the salience map. Using this salience map, we also define adaptive structuring functions. We also present the applicability of adaptive mathematical morphology to image regularization. The connection between adaptive mathematical morphology and Lasry-Lions regularization of non-smooth functions provides an elegant tool for image regularization.
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| 6. |
- Curic, Vladimir, et al.
(författare)
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Salience adaptive structuring elements
- 2012
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Ingår i: IEEE Journal on Selected Topics in Signal Processing. - 1932-4553 .- 1941-0484. ; 6:7, s. 809-819
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Tidskriftsartikel (refereegranskat)abstract
- Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Morphological operators with salience adaptive structuring elements shift edges with high salience to a less extent than those with low salience. Salience adaptive structuring elements are less flexible than morphological amoebas and their shape is less affected by noise in the image. Consequently, morphological operators using salience adaptive structuring elements have better properties.
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| 7. |
- Curic, Vladimir, et al.
(författare)
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Salience-Based Parabolic Structuring Functions
- 2013
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Ingår i: Mathematical Morphology and Its Applications to Signal and Image Processing. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642382932 ; 7883, s. 183-194
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Konferensbidrag (refereegranskat)abstract
- It has been shown that the use of the salience map based on the salience distance transform can be useful for the construction of spatially adaptive structuring elements. In this paper, we propose salience-based parabolic structuring functions that are defined for a fixed, predefined spatial support, and have low computational complexity. In addition, we discuss how to properly define adjunct morphological operators using the new spatially adaptive structuring functions. It is also possible to obtain flat adaptive structuring elements by thresholding the salience-based parabolic structuring functions.
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| 8. |
- Fakhrzadeh, Azadeh, et al.
(författare)
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Analyzing Tubular Tissue in Histopathological Thin Sections
- 2012
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Ingår i: 2012 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING TECHNIQUES AND APPLICATIONS (DICTA). - : IEEE conference proceedings. ; , s. 1-6
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Konferensbidrag (refereegranskat)abstract
- We propose a method for automatic segmentation of tubules in the stained thin sections of various tissue types. Tubules consist of one or more layers of cells surrounding a cavity. The segmented tubules can be used to study the morphology of the tissue. Some research has been done to automatically estimate the density of tubules. To the best of our knowledge, no one has been able to, fully automatically, segment the whole tubule. Usually the border between tubules is subtle and appears broken in a straight-forward segmentation. Here we suggest delineating these borders using the geodesic distance transform. We apply this method on images of Periodic Acid Shiffs (PAS) stained thin sections of testicular tissue, delineating 89% of the tubules correctly.
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