Showing papers on "Structuring element published in 2004"

Opening and Closing

Abstract: The erosion of an image not only removes all structures that cannot contain the structuring element but it also shrinks all the other ones. The search for an operator recovering most structures lost by the erosion leads to the definition of the morphological opening operator. The principle consists in dilating the image previously eroded using the same structuring element. In general, not all structures are recovered. For example, objects completely destroyed by the erosion are not recovered at all. This behaviour is at the very basis of the filtering properties of the opening operator: image structures are selectively filtered out, the selection depending on the shape and size of the SE. The dual operator of the morphological opening is the morphological closing. Both operators are at the basis of the morphological approach to image filtering developed in Chap. 8.

Automated 2-D building footprint extraction from high-resolution satellite multispectral imagery

Abstract: A fully automated algorithm for the extraction of building footprints from commercial high-resolution satellite imagery is presented. The algorithm is based on identifying buildings and their shadows in the differential morphological profile (DMP) of 1-m resolution panchromatic imagery. The DMP is a multi-scale image analysis technique where an image profile is constructed through the use of morphological opening and closing operations while varying the size of the structuring element. A variety of shape-based features are utilized to extract buildings and their shadows from the DMP. The algorithm has been tested on an IKONOS image, and the results are promising.

Optimization of gray scale morphological opening for noise removal in texture images

Abstract: Application of opening, which is a basic operation of mathematical morphology, often yields undesired results like the occurrence of artifacts. This problem can be avoided by using a gray scale structuring element resembling the objects in the target image. Since a texture image is composed of an arrangement of similar small objects, it is possible to derive such a gray scale structuring element by estimating one representative gray scale object from those arranged in the texture image. In this paper, an estimation method of the optimal gray scale structuring element using "primitive, grain, and point configuration (PGPC)" texture model is proposed.

Method of filtering an image for high precision machine vision metrology

Abstract: A structured morphology filtering method is disclosed for filtering an image for high precision machine vision metrology using specifically-determined structuring elements to precisely preserve the location of specific features in the filtered image. A selected structuring element shape generally exhibits geometric similarity with at least a portion of the feature to be preserved in the filtered image. The structuring element may be oriented to corresponds to the orientation of the feature to be inspected. For example, for a linear feature to be inspected, the optimal structuring element is a line or narrow rectangle at the same orientation, while for images of circles, it is a circle. The orientation of the structuring element may be determined or adjusted automatically during a set of automatic inspection operations, based on an automatic determination of the orientation of the feature to be inspected.

Morphological gradient operators for colour images

Abstract: A new morphological gradient operator for colour images is introduced that can be viewed as a direct extension of the well known morphological gradient. In this approach, each pixel is considered as multivariate data and its output is the maximum distance between any two points within a structuring element, determined by a norm. In contrast with other nonlinear schemes, this approach reduces to the morphological gradient for single channel images. It is also computationally efficient and responds well to step edges. To overcome, any sensitivity to noise a robust colour morphological gradient operator is proposed that rejects outlying vector pairs before determining the maximum distance. Results show the effectiveness of the techniques.

Morphological decomposition of sandstone pore–space: fractal power-laws

Abstract: Morphological decomposition procedure is applied to estimate fractal dimension of a pore–space, which is isolated from a sandstone microphotograph. The fractal dimensions that have been computed by considering various probing rules have precisely followed the universal power-law relationships proposed elsewhere. These results are derived by considering structuring elements such as octagon, square and rhombus that have been used to decompose the pore– space of sandstone image. The radii of the structuring elements are made to increase in a cyclic fashion. To perceive the decomposed pore image, a color-coding scheme is adapted, from which one can identify several sizes of these structuring elements that could be fit into this pore. This exercise facilitates testing of the relationship between the radius of the structuring elements that could be used to decompose the pore at different levels, and the number of decomposed shapes that could be fit into the pore while using the corresponding structuring element. From the number–radius relationship, the fractal dimensions of pore–space estimated, by considering these structuring elements, yield the values of 1.82, 1.76, and 1.79. These values are in conformity with the values arising from estimation of box dimension method, as well as the dimensions of the corresponding pore connectivity networks (PCNs). 2003 Elsevier Science Ltd. All rights reserved.

Structure Characterization Using Mathematical Morphology

Abstract: This thesis deals with the application of mathematical morphology to images of some kind of structure, with the intention of characterizing (or describing) that structure. The emphasis is placed on measuring properties of the real-world scene, rather than measuring properties of the digital image. That is, we require that the measurement tools are sampling-invariant, or at least produce a sampling-related error that is as small as possible. Filters defined by mathematical morphology can be defined both in the continuous space and the sampled space, but will produce different results in both spaces. We term these differences "discretization errors". Many of the results presented in this thesis decrease the discretization errors of morphological filters.

Control of variable structure elements in adaptive mathematical morphology for boundary enhancement of ultrasound images

Abstract: This paper discusses boundary enhancement function for adaptive morphology using variable structuring elements. The mechanism for boundary enhancement is quantitatively described. A method is proposed for setting the definition domain for the structuring elements and controlling their values, which is effective regarding boundary enhancement and speckle reduction in ultrasound images. It is shown that by controlling the value of the structuring element so that it is large near the boundary and small in other areas of the image, boundary enhancement and speckle elimination can be performed simultaneously, using the opening operation and closing operation. The spatial resolution and statistical properties of the speckle intensity in the ultrasound image are utilized to set these functions automatically on the basis of information on the object image. The effectiveness of the proposed method is demonstrated by a quantitative evaluation of a numerical phantom created in a computer simulation and in an application to boundary extraction from a real biological ultrasound image. It is shown that the performance of the proposed method in speckle reduction and boundary enhancement is better than that of the conventional method. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 87(11): 20–33, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20117

Structuring Element Representation of an Image and Its Applications

Abstract: In this paper we present the linear combination of a fuzzy opening and closing filter with locally adaptive structuring elements that can preserve the geometrical features of an image. Based on the adaptation algorithm of linear combination of the fuzzy opening and closing filter, the optimal structuring element for image representation is obtained. The optimal structuring element is an indicator of the shape and direction of an object's image, which is useful in filtering, multi resolution, segmentation, and recognition of an image.

A kind of omni-directional multi-angle structuring elements adaptive morphological filters

Abstract: According to the structure characteristic of the morphological filter and combining the open-closing (close-opening) compound operation with adaptive arithmetic, this paper presents a kind of method that can not only efficiently removed various noise in images which have the complex texture but also preserved the detail better. The results of simulation show that it is superior to the standard median filter, the maximal, minimal morphological filter with onmi-directional structuring elements in the aspect of the noise removal, thereby extending the application of the morphological filters in removing the Gaussian noise. What is the most important is that this algorithm can keep the details of images more effectively.

Color image morphology using an adaptive saturation-based technique

Abstract: An adaptive algorithm that implements a saturation-based ordering (for color image morphology) is introduced. The adaptation is achieved using a tradeoff parameter in the form of a nonlinear function of the local saturation. To evaluate the performance of the proposed algorithm, a deigned psychophysical experiment is used to derive a metric denoted as the average value for the psychophysical evaluation in percent (APE%). Results of implementing the proposed APE show that an APE=73 to 96% can be achieved for basic morphological operators, i.e., dilation, erosion, opening, and closing. APE value depends on the size and shape of the structuring element as well as on the image details. The proposed algorithm has also been extended to other morphological operators, such as image smoothing (noise suppression), top hat, gradient, and Laplacian operators. In the case of a smoothing operation, an average peak signal-to-noise ratio (PSNR)=31 to 37 dB is achieved at various structuring elements and applied noise variances, while good results are achieved with the proposed top-hat operators.

Smooth Surface Reconstruction Using Tensor Fields as Structuring Elements

Abstract: We propose a new strategy to estimate surface normal information from highly noisy sparse data. Our approach is based on a tensor field morphologically adapted to infer normals. It acts as a three-dimensional structuring element of smooth surfaces. Robust orientation inference for all input elements is performed by morphological operations using the tensor field. A general normal estimator is defined by combining the inferred normals, their confidences and the tensor field. This estimator can be used to directly reconstruct the surface or give input normals to other reconstruction methods. We present qualitative and quantitative results to show the behavior of the original methods and ours. A comparative discussion of these results shows the efficiency of our propositions.

An adaptive soft-morphological-gradient-filter-for-edge-detection

Abstract: In this paper, a novel adaptive soft morphological gradient (ASMG) filter is proposed, based on a combination of the idea of the soft morphological filtering and the adaptive technique ASMG filtering is an efficient nonlinear sharpening method, which can be applied for edge detection By employing four directional structuring elements, ASMG filtering has the capability of selecting the directional structuring element with the maximum response, whose direction varies depending on the change of directional edges In addition, by comparing the variance of the moving structuring window with the base variance, the ASMG filter provides an adaptive algorithm for morphological operations The experimental results show that the ASMG filter is better than the traditional operators in edge detection and noise suppression

Image edge detection algorithm of mathematical morphology based on VC++6.0

Abstract: The theory of mathematical morphology is applied based on VC++6.0. VC++6.0 has the characteristics of ripe software techniques such as efficient, inheritance, encapsulation and portability, which can substitute Matlab, the commonly used image-processing tool. An image processing applied software, which is fast, accurate and flexible, could be developed in VC++6.0. the edge detection can be gained for any gray-scale image with that.

3-d morphological operations with adaptive structuring elements for clustering of significant coefficients within an overcomplete wavelet video coding framework

Abstract: A system and method is provided for digitally encoding video signals within an overcomplete wavelet video coder. Three dimensional morphological operations are used to identify clusters of significant wavelet coefficients. A video coding algorithm unit 365 locates significant wavelet coefficients across space and time. The video coding algorithm unit [365] also uses motion information to locate significant wavelet coefficients across space and time in a direction of motion. The lengths of a three dimensional structuring element [500] may be adaptively varied depending upon characteristics of the underlying video data. The invention increases coding efficiency and provides an increased quality of decoded video.

Gray Scale Morphology Using Double Structuring Elements and Their Application to Contrast Enhancement for Ultrasound Images

Abstract: We discuss a new morphological operations using double structuring elements (DSEs) and apply them to edge sharpening of the ultrasound images with speckle. The DSEs, a couple of two different structuring elements, varying with the local characteristics of the processing image, yield an edge-sharpening effect, which general single structuring element does not have. Our method sharpens the boundary without speckle emphasis, overshoot nor undershoot because it is based on geometrical characteristics of the image components.

Morphological image sharpening by double structuring elements for ultrasound images

Abstract: We discuss a new morphological operations using double structuring elements (DSEs) and apply them to image sharpening of ultrasound B-mode images with speckle pattern. The DSEs, a couple of two different structuring elements, varying with the local characteristics of the input image, yield an edge-sharpening effect. General single structuring element does not have the sharpening function. Our method improves contrast at the tissue boundary without speckle emphasis and does not generate overshoot nor undershoot around the boundary. We demonstrate its effectiveness in experiments using human thyroid images.

Texture primitives description and segmentation using variography and mathematical morphology

Abstract: In this paper, we propose a novel method of optimizing texture primitives description and segmentation using variography. Indeed, successful textural analysis relies on the careful selection of the adapted window size. The variogram is essentially a "variance of differences" in the values as a function of the separation distance. This variance therefore changes as the separation distance increases where repetitive structures are described as hole-effects. We used the local minima (hole-effects) to find size, shape an orientation of unit pattern of image textures and thus to determine the optimal structuring element which is used in mathematical morphological texture analysis. Some of Brodatz's natural texture images have been used for evaluating the performance of this method. The structuring elements found are well adapted for the characterization and discrimination of the texture aspects of images. Furthermore, we performed a textural segmentation using the variogram characteristics. Promising results are obtained and presented.

Object extraction based on evolutionary morphological processing

Abstract: This paper introduces a novel technique for object detection using genetic algorithms and morphological processing. The method employs a kind of object oriented structure element, which is derived by genetic algorithms. The population of morphological filtersis iteratively evaluated according to a statistical performance index corresponding to object extraction ability, and evolves into an optimal structuring element using the evolution principles of genetic search. Experimental results of road extraction from high resolution satellite images are presented to illustrate the merit and feasibility of the proposed method.

Machine vision system for automatic inspection of surface defects in aluminium die casting

Abstract: A machine vision system is presented for the automatic inspection of surface defects in aluminium die casting. The system uses a hybrid image processing algorithm based on mathematic morphology to detect defects with different sizes and shapes. The defect inspection algorithm consists of two parts. One is a parameter learning algorithm, in which a genetic algorithm is used to extract optimal structuring element parameters, and segmentation and noise removal thresholds. The second part is a defect detection algorithm, in which the parameters obtained by a genetic algorithm are used for morphological operations. The machine vision system has been applied in an industrial setting to detect two types of casting defects: parts mix-up and any defects on the surface of castings. The system performs with a 99% or higher accuracy for both part mix-up and defect detection and is currently used in industry as part of normal production.

FPGA implementation of fuzzy morphological filters

Abstract: In this paper, we consider a natural paradigm for lifting of crisp-set binary filters to fuzzy filters for hardware implementation and process the gray-scale realizations of binary images as [0,1]-valued fuzzy binary images We present the implementation of the filtering algorithms for smoothing, peak detection and edge detection of such fuzzy images using the Xilinx Virtex series of FPGA for real-time processing of image sequences The erosion filter forms the core for all of the filtering algorithms and the dilation filter itself is implemented as a function of the erosion filter Smoothing is achieved using fuzzy opening of the input image using the user defined fuzzy structuring element A fuzzy top-hat transform is used for peak detection As opposed to gray-scale top-hat, which detects only the narrow peaks, the fuzzy top-hat is shown to detect both the narrow as well as wide peaks within the same image Edge detection algorithm uses the fuzzy morphological gradient wherein the set minus operation has been performed between the dilated and the eroded images Pipelined architectures are used for the erosion filter design and the use of flops has been maximized to achieve a high clock rate The throughput measurements and the results generated by the implemented filters are also presented

A pests recognition system based on mathematical morphology and neural network

Abstract: In this paper, Mathematical Morphology is applied to plant diseases and insect pests recognition for the first time, and the operations of dilation and erosion by a structuring element are implemented by a fast algorithm. According to the quadrature feature of different pests skeletons, a new method of insect pests recognition based on the combination of Mathematical Morphology and Neural Networks is proposed. The experiment results have shown that Mathematical Morphology has good performance for feature extraction and this proposed method is more effective in recognizing pests than using Neural Networks directly.

Optical implementations of threshold decomposition and morphological operations with dual-rail processing

Abstract: Fast parallel processing of gray-scale images and exact hard-clip thresholding are two important functionalities necessary in optoelectronic implementations of structural processors. The parallel nature of processing stems from optical implementation of local operations with arrays of active smart pixels. We have demonstrated a morphological image processor composed of arrays of bistable optoelectronic transceivers which are connected in differential pairs and work as comparators. The use of differential pairs of optical thyristors fabricated in GaAs technology allows to realize a dual rail architecture for this photonic morphological image processor. The processor consists of a thresholding module and a binary morphological processing module. The thresholding module decomposes gray level images into series of binary slices. In the binary morphological processing module operations are performed within a neighborhood defined by a structuring element implemented as a diffractive fan-out element. In the prototype set-up we demonstrate median filtering, dilation and erosion operations performed for an image of 8x8 pixels and threshold decomposition of 6 gray level images. In principle all rank order as well as morphological filters can be optically calculated in the set-up. Additional functionality of the processor is achieved with use of the electronic layer with digital cellular processors. The electronic layer, designed as an array of simple digital processors, realizes a set of operations on binary images using 4 bit programmable weights. Simulation results for 0.8 µm CMOS technology are presented. We discuss the limitations of the photonic morphological image processing with respect to bandwidth, parallelism and architecture of the processor.

Optimizing Texture Primitives Description Based on Variography and Mathematical Morphology

Abstract: This paper proposes a novel method of optimising texture primitives detection based on the mathematical morphology. Indeed, successful textural analysis relies on the careful selection of the adapted window size. We use variography to optimise the shape of structuring elements to fit the shape of the unit patterns that form a texture. The variogram is essentially a “variance of differences” in the values as a function of the separation distance. This variance therefore changes as the separation distance increases where repetitive structures are described as hole-effects. We used the local minima (hole-effects) to find size, shape an orientation of unit pattern of image textures and thus to determine the optimal structuring element which will be used in mathematical morphological texture analysis. Some of Brodatz’s natural texture images have been used for evaluating the performance of the structuring elements found in the characterisation and discrimination of the texture aspects of images. Promising results are obtained and presented.

Structuring professional cooperation

Abstract: We present an element suitable to structure professional cooperation. This structuring element is independent of any domain or area of expertise, although it is biased towards design. The element describes modes of operation of a single expert and the cooperation between multiple experts. Based on this, aggregates representing complex project situations can be rendered. We offer several examples.

Graph-based representation for 2-D shape using decomposition scheme

Abstract: In this paper, to represent 2-D shape as a relational structure, i.e. graph, we propose a new shape decomposition scheme composed of two stages: first, a given shape is decomposed into meaningful parts by using the constrained morphological decomposition (CMD) in a recursive manner. More specifically, the CMD adopts the use of the opening operation with the ball-shaped structuring element and the weighted convexity to select the optimal decomposition. Second, the iterative merging stage provides a compact graph-based representation based on the weighted convexity difference. From the experimental results for various and modified 2-D shapes, it is believed that the graph-based representation for 2-D shape coincides with that based on human insight, and also provides robustness to scaling, rotation, noise, shape deformation and occlusion.

Narrow branch preservation in morphological reconstruction

Abstract: We present a morphological approach to the reconstruction of fine branching structures in three dimensional data, developed from the basic procedures of reconstruction by dilation. We address a number of closely related questions arising from this reconstruction goal, including issues of structuring element size and shape, noise propagation, iterated approaches, and the relationship between geodesic and conditional dilation. We investigate and assess the effect and importance of these considerations in the context of the overall reconstruction process, and examine the effectiveness of the approach in addressing the task of reconstructing narrow branch features in noisy data.