Showing papers on "Structuring element published in 2015"

A new structuring element for multi-scale morphology analysis and its application in rolling element bearing fault diagnosis

Abstract: The condition monitoring and fault diagnosis of rolling element bearings play an important role in the safe and reliable operation of rotating machinery. Feature extraction based on vibration signals is an effective means to identify the operating condition of rolling element bearings. Methods based on multi-scale mathematical morphology (MM) have recently been developed to extract features from one-dimensional signals. In this paper, a new double-dot structuring element (SE) is constructed for multi-scale MM. A pattern spectrum, obtained from the multi-scale MM, is used as a feature extraction index. A correlation analysis gives the final identification result by utilizing information over a whole pattern spectrum. Compared with the most commonly used flat SE, the double-dot SE can extract more features of original signals at different scales. Vibration signals, measured from defective bearings with outer race faults, inner race faults and ball faults, are used to evaluate the fault detection ability of ...

Normalization of TanDEM-X DSM Data in Urban Environments With Morphological Filters

Abstract: The TanDEM-X mission (TDM) is a spaceborne Radar interferometer which delivers a global digital surface model (DSM) with an unprecedented spatial resolution. This allows resolving objects above ground such as buildings. Extracting and characterizing those objects in an automated manner represents a challenging problem but opens simultaneously a broad range of large-area applications. In this paper, we discuss and evaluate the suitability of morphological filters (MFs) for the derivation of normalized DSMs from the TDM in complex urban Environments and introduce a novel region-growing-based progressive MF procedure. This approach is jointly proposed and can be combined with a postclassification processing scheme to specifically allow for a viable reconstruction of urban morphology in a challenging terrain. The filter approach comprises a multistep procedure using concepts of morphological image filtering, region growing, and interpolation techniques. Therefore, it extends the idea of progressive MFs. The latter aim to identify nonground pixels in the DSM by gradually increasing the size of a structuring element and applying iteratively an elevation difference threshold. After the identification of initial nonground pixels, here, potential nonground pixels are identified within each iteration, and their similarity with respect to neighboring nonground pixels is assessed. Pixels are finally labeled as nonground if a constraint is fulfilled. The postclassification processing scheme adapts techniques of object-based image analyses to further refine regions of classified nonground pixels. Digital terrain models are subsequently generated by interpolating between identified ground pixels. Experimental results are obtained for settlement areas that cover large parts of the cities of Izmir (Turkey) and Wuppertal (Germany). They confirm the capability of the proposed approaches for a reduction of omission errors compared to basic MF-based methods when classifying ground pixels, which is favorable in a mountainous Terrain with steep slopes.

An approach to fault location in HVDC lines using mathematical morphology

Abstract: This paper presents an approach to fault location in HVDC transmission lines. A superimposed signal calculated from voltages and currents sampled in the same terminal is processed by a morphological filter in order to highlight the wavefronts and allow the fault location. The morphological filter was adopted due to its simplicity and low computational cost. A suitable combination of superimposed signal, morphological filter and Structuring Element (SE) enabled developing a simple algorithm to detect the correct wavefronts and, consequently, estimate the fault position. The results were obtained considering data sampled in one or two terminals. The influence of the main fault parameters as well as the approach parameters were evaluated and the results are promising.

Perceptual color hit-or-miss transform: application to dermatological image processing

Abstract: The hit-or-miss transform is a mathematical morphological processing designed to find objects in image. Its extension to grayscale domain is not unique, but Barat’s method is the most appropriate to find specific objects with bandwidth in space and color evolutions. This tolerance is possible with the use of non-flat structuring elements. In this paper, a color extension of the Barat’s method is presented. For this purpose, a new mathematical morphology method, based on the concept of convergence in the CIELAB space and where the definition of non-flat structuring elements is possible, is used. A comparison with the existing approaches in the literature is done. Results are given and commented on synthetic and real images.

Analysis of fuzzy morphology in spore counts of mycorrhizal fungi

Abstract: Mathematical Morphology presents a systematic model to extract geometric features of images using morphological operators that transform the original image into another, using a third image called structuring element. Fuzzy mathematical morphology extends morphological operators for images in grayscale and colored ones, using the theory of fuzzy sets, especially fuzzy logics, where operators are defined using the notions of R-implications and T-norms. In this work, an automatic method was proposed for counting mycorrhizal fungi spores. Spores counting is done manually using a ribbed plate and a stereomicroscope. This paper proposes an automatic method for counting spores by using Godel morphology. It provides a comparison with a method using neural network.

An Approach to Adaptive Quadratic Structuring Functions Based on the Local Structure Tensor

Abstract: Classical morphological image processing, where the same structuring element is used to process the whole image, has its limitations. Consequently, adaptive mathematical morphology is attracting more and more attention. So far, however, the use of non-flat adaptive structuring functions is very limited. This work presents a method for defining quadratic structuring functions from the well known local structure tensor, building on previous work for flat adaptive morphology. The result is a novel approach to adaptive mathematical morphology, suitable for enhancement and linking of directional features in images. Moreover, the presented strategy can be quite efficiently implemented and is easy to use as it relies on just two user-set parameters which are directly related to image measures.

Blood vessel extraction with optic disc removal in retinal images

Abstract: Automatic extraction of retinal blood vessels is an important issue for the diagnosis and the treatment of different retinal disorders. Most of the retinal images are of low contrast due to non-uniform illumination during acquisition process. Therefore, vessel extraction from unevenly illuminated retinal background is really a challenging task. To extract the vessels which lie in the optic disc region, the removal of the optic disc is also important. This paper proposes an algorithm for automatic blood vessel extraction and optic disc removal on poorly illuminated retinal images using curvelet transform, morphological operation, matched filtering and fuzzy entropy maximization. Curvelet transform is used to extract the finest details along the vessels since it can represent the lines, the edges, the curvatures, the missing and the imprecise boundary details efficiently. To remove the optic disc, the curvelet based edge enhanced image is first opened by a disk shaped structuring element which is then subtracted from the inverted histogram equalized image. Matched filtering intensifies the blood vessels' response in the enhanced image. The multiple threshold values for the maximum matched filter response that maximize the fuzzy entropy are considered to be the optimal thresholds to extract the different types of vessel silhouettes from the background. Differential Evolution algorithm is used to obtain the optimal combination of the fuzzy parameters. Performance evaluated on publicly available DRIVE database demonstrate that the present work outperforms the existing works for various types of vessels extraction and optic disc removal even from poorly illuminated retinal images.

A gradient-based morphological method to produce planar curve offsets

Abstract: Two-dimensional curve offsets have a wide application area ranging from manufacturing to medical imaging. To that end, this paper concentrates on two novel techniques to produce planar curve offsets. Both methods, which are based on mathematical morphology, employ the concept that the boundaries formed by a circular structuring element whose center moves across the points on a base curve comprise the entire offsets of the progenitor. The first technique titled IMOBS was introduced in our former paper and was shown to have superior properties in terms of its high accuracy, low computational complexity, and its ability to handle complex curves if compared to the techniques available in the literature. Consequently, an all-purpose algorithm titled AMOBS is introduced to enhance further the performance of the former technique by making good use of gradient information to find globally the most suitable candidate points in the boundary data set via grid search techniques. Thus, the new paradigm is demonstrated to overcome some of the problems (like orphan curve offsets) encountered in extreme cases. Both algorithms, which have similar attributes in terms of run-time complexity and memory cost, are comparatively tested via two experimental cases where most CAD/CAM packages fail to yield acceptable results.

Supervised Building Extraction Using Morphological Profiles with Adaptive Structures

Abstract: Morphological profiles are one of the highly effective tools for image classification when structural information is critical Morphological profiles, however create high dimensional feature space and increase the complexity of classifier In this paper we have quantitatively evaluated the fact that the classification accuracy of each profile is dependent on the size and shape of the structuring element We propose a classification scheme which uses morphological profiles with adaptive structuring element We relate the shape and size of structuring element which is used for producing morphological profiles with the discrete wavelet transform of the image The size and shape of structuring element adapts to the frequency content of the pixel's neighborhood With this adaptive structuring element we can produce a single profile which is quite effective for classification The results show that with proposed scheme significant improvement was obtained in the classification accuracy with reduced dimensionality of feature space

Morphologically filtered power-normalized cochleograms as robust, biologically inspired features for ASR

Abstract: In this paper, we present advances in the modeling of the masking behavior of the human auditory system (HAS) to enhance the robustness of the feature extraction stage in automatic speech recognition (ASR). The solution adopted is based on a nonlinear filtering of a spectro-temporal representation applied simultaneously to both frequency and time domains---as if it were an image---using mathematical morphology operations. A particularly important component of this architecture is the so-called structuring element (SE) that in the present contribution is designed as a single three-dimensional pattern using physiological facts, in such a way that closely resembles the masking phenomena taking place in the cochlea. A proper choice of spectro-temporal representation lends validity to the model throughout the whole frequency spectrum and intensity spans assuming the variability of the masking properties of the HAS in these two domains. The best results were achieved with the representation introduced as part of the power normalized cepstral coefficients (PNCC) together with a spectral subtraction step. This method has been tested on Aurora 2, Wall Street Journal and ISOLET databases including both classical hidden Markov model (HMM) and hybrid artificial neural networks (ANN)-HMM back-ends. In these, the proposed front-end analysis provides substantial and significant improvements compared to baseline techniques: up to 39.5% relative improvement compared to MFCC, and 18.7% compared to PNCC in the Aurora 2 database.

Retinal Vessel Detection Based on Fuzzy Morphological Line Enhancement

Abstract: The paradigm of Fuzzy Morphology extends the concept of binary morphology to handle grayscale images. Fuzzy Morphology provides meaningful, local and simple operations that, when properly combined, form powerful transformations. We use this approach to segment out vessels in eye-fundus images, which can be used to diagnose medical conditions such as diabetic retinopathy. To automatically estimate the presence of such conditions, distinguishing vessels from other artifacts becomes a necessary initial step. To address the problem of segmenting curvilinear-like objects such as vessels, our methodology consists on applying the same structuring element rotated several times. We construct a vessel segmentation method and compare it with current state-of-the-art alternatives, showing the potential of our approach.

When Convex Analysis Meets Mathematical Morphology on Graphs

Abstract: In recent years, variational methods, i.e., the formulation of problems under optimization forms, have had a great deal of success in image processing. This may be accounted for by their good performance and versatility. Conversely, mathematical morphology (MM) is a widely recognized methodology for solving a wide array of image processing-related tasks. It thus appears useful and timely to build bridges between these two fields. In this article, we propose a variational approach to implement the four basic, structuring element-based operators of MM: dilation, erosion, opening, and closing. We rely on discrete calculus and convex analysis for our formulation. We show that we are able to propose a variety of continuously varying operators in between the dual extremes, i.e., between erosions and dilation; and perhaps more interestingly between openings and closings. This paves the way to the use of morphological operators in a number of new applications.

Viscous-Hyperconnected Attribute Filters: A First Algorithm

Abstract: In this paper a hyperconnectivity class that tries to address the leakage problem typical of connected filters is used. It shows similarities with the theory of viscous lattices. A novel algorithm to perform attribute filtering of viscous-hyperconnected components is proposed. First, the max-tree of the image eroded by a structuring element is built: it represents the hierarchy of the cores of the hyperconnected components. Then, a processing phase takes place and the node attributes are updated consistently with the pixels of the actual hyperconnected components. Any state-of-the-art algorithm can be used to build the max-tree of the component cores. An issue arises: edges of components are not always correctly preserved. Implementation and performance are presented. A possible solution is put forward and it will be treated in future work.

Morphological Image Processing GUI using MATLAB

Abstract: In this paper, we present an overview of Morphological Image Processing and edge detection using gradient based on different operators in MATLAB and developed its GUI (Graphical User Interface). This paper describes the basic technological aspects of Digital Image Processing with reference to Morphological techniques used in image processing. The word morphology commonly denotes a branch of biology that deals with the form and structure of animals and plants. Morphological processing refers to certain operations where an object is hit with a structuring element and thereby reduced to a more revealing shape . Morphology is related to the shapes and digital morphology is a way to describe and analyze the shape of a digital object in image processing. Morphological image processing GUI deals with the detection of X-Ray images and its edge detection process. The complete image processing is done using MATLAB Graphical User Interface Development Environment (GUIDE).

A theoretical insight into morphological operations in surface measurement by introducing the slope transform

Abstract: As one of the tools for surface analysis, morphological operations, although not as popular as linear convolution operations (e.g., the Gaussian filter), are really useful in mechanical surface reconstruction, surface filtration, functional simulation, etc. By introducing the slope transform originally developed for signal processing into the field of surface metrology, an analytic capability is gained for morphological operations, paralleling that of the Fourier transform in the context of linear convolution. Using the slope transform, the tangential dilation is converted into the addition in the slope domain, just as by the Fourier transform, the convolution switches into the multiplication in the frequency domain. Under the theory of the slope transform, the slope and curvature changes of the structuring element to the operated surface can be obtained, offering a deeper understanding of morphological operations in surface measurement. The analytical solutions to the tangential dilation of a sine wave and a disk by a disk are derived respectively. An example of the discretized tangential dilation of a sine wave by the disks with two different radii is illustrated to show the consistency and distinction between the tangential dilation and the classical dilation.

Performance and time requirement analysis of top-hat transform based small target detection algorithms

Abstract: Top-Hat transform is well known background suppression method used in small target detection. In this paper, we investigate various different Top-Hat transformation based small target detection approaches. All of the methods are implemented with their best parameter settings and applied to the same test image. The comparison among them is done in terms of three issues: 1. the detection performance (precision and false alarm rate), 2. the time requirement of the method and its usability for real time applications, 3. the number of parameters, which need user interaction. Results show that all of the algorithms require a prior knowledge of target size, which is either used as the structuring element size or as the threshold for post-processing. Algorithms, which use automatic approaches to select its parameters, are not generic to be applied to various images. But algorithms, which use adaptive methods for deciding on the threshold value, perform better than the others.

Enhanced Contrast of Reconstructed Image for Image Secret Sharing Scheme Using Mathematical Morphology

Abstract: Visual secret sharing (VSS) is one of the cryptographic techniques of Image secret sharing scheme (ISSS) that performs encoding of secret message image (text or picture) into noise like black and white images, which are called as shares. Shares are stacked together and secret message image is decoded using human visual system. One of the major drawbacks of this scheme is its poor contrast of the recovered image, which improves if computational device is available while decoding. In this paper, we propose to improve poor contrast of classical VSS schemes for text or alphanumeric secret messages and low entropy images. Initially, stacked image is binarized using dynamic threshold value. A mathematical morphological operation is applied on the stacked image to enhance contrast of the reconstructed image. Moreover, a method is proposed that allows the size of the structuring element to change according to the contrast and the size of a stacked image. We perform experiments for different types of VSS schemes, different share patterns, different share types (rectangle and circle), and low entropy images. Experimental results demonstrate the efficacy of the proposed scheme.

Structuring contents of a meeting

Abstract: An apparatus is configured to structure contents of a meeting. The apparatus includes a voice recognizer configured to recognize a voice to generate text corresponding to the recognized voice, and a clustering element configured to cluster the generated text into subjects to generate one or more clusters. The apparatus further includes a concept extractor configured to extract concepts of each of the generated clusters, and a level analyzer configured to analyze a level of each of the extracted concepts. The apparatus further includes a structuring element configured to structure each of the extracted concepts based on the analysis.

Partial Fingerprint Image Enhancement using Region Division Technique and Morphological Transform

Abstract: Fingerprints are the most renowned biometric trait for identification and verification. The quality of fingerprint image plays a vital role in feature extraction and matching. Existing algorithms work well for good quality fingerprint images and fail for partial fingerprint images as they are obtained from excessively dry fingers or affected by disease resulting in broken ridges. We propose an algorithm to enhance partial fingerprint images using morphological operations with region division technique. The proposed method divides low quality image into six regions from top to bottom. Morphological operations choose an appropriate Structuring Element (SE) that joins broken ridges and thus enhance the image for further processing. The proposed method uses SE “line” with suitable angle 𝜃 and radius 𝑟 in each region based on the orientation of the ridges. The algorithm is applied to 14 low quality fingerprint images from FVC-2002 database. Experimental results show that percentage accuracy has been improved using the proposed algorithm. The manual markup has been reduced and accuracy of 76.16% with Equal Error Rate (EER) of 3.16% is achieved.

Morphological Image Processing

Abstract: This paper presents an Morphological image processing is constructed with operations on sets of pixels. Binary morphology uses only set membership and is different to the different values such as image, color of a pixel. We will examine some basic set operations and their usefulness in image processing and we will deal here only with Morphological filtering operators such as Erosion, dilation, Opening, closing Hit-or-miss Boundary extraction. Morphological operations for binary images and its applications.

Multiple Attenuation Based on Mathematical Morphology Filtering Method

Abstract: Multiple attenuation is a troublesome problem in many seismic exploration areas. Current multiple suppression technique include two kinds of method: filter-based method and prediction-based method. However, these methods are powerless when the energy of multiples and primaries are mixed. Therefore, we introduce mathematical morphology method to seismic exploration as a new method to solve this problem. We found that multiples have similar seismic wavelet with that of primary reflection, and also have distinct seismic event. These seismic events give us a chance to distinguish the multiples and the primary reflections. Morphological filter is based on multiscale decomposition method. It use different structuring element to separate the multiples and the primary reflection clearly, and thus making multiple attenuation as well as saving subtle signal of primary reflection. In this abstract, we illustrate this method and give an examples of its application in synthetic and real data.

Location Time of Power Quality Disturbances and Noise Using Morphology Gradient and Skeletonization in 3D

Abstract: In power system, there are some disturbances such as, voltage dip, momentary interruption, voltage swell, or oscillatory transients that may result in mal-function or failure in operation of some devices. Knowing the location where the disturbances occur in the system is an essential part in selecting the appropriate method on improving power quality issues in order to get effective and efficient results. One of methods in locating power quality disturbances is using Mathematical Morphology (MM). In this paper, signals with disturbances were filtered using morphology gradient. Top-hat transform is applied for the filtered signal using flat structuring element. The simulation results show that the location of disturbances can be detected accurately. Skeletonization is used to identify the location time of the noises in the system. By plotting the results in 3D, it makes easier to identify the location of disturbances with or without noises from their different color and shape as pattern recognition.

Morphological processing of videostream frames binary masks

Abstract: One of the primary tasks of videoframes processing of digital videostreams is to quantify the geometric structure of moving objects, in order to extract information from videostreams frames. In this paper we purpose a recursive algorithms that are based on morphological conditional dilation and conditional erosion operations. Practical implementation of purposed algorithms on real-time video sequences shows, that computational complexity of purposed algorithms is equal to m+1, where m — number of pixels in kernel.

Fast algorithms for morphological operations using run-length encoded binary images.

Abstract: This paper presents innovative algorithms to efficiently compute erosions and dilations of run-length encoded (RLE) binary images with arbitrary shaped structuring elements. An RLE image is given by a set of runs, where a run is a horizontal concatenation of foreground pixels. The proposed algorithms extract the skeleton of the structuring element and build distance tables of the input image, which are storing the distance to the next background pixel on the left and right hand sides. This information is then used to speed up the calculations of the erosion and dilation operator by enabling the use of techniques which allow to skip the analysis of certain pixels whenever a hit or miss occurs. Additionally the input image gets trimmed during the preprocessing steps on the base of two primitive criteria. Experimental results show the advantages over other algorithms. The source code of our algorithms is available in C++.

To Enhance the Medical Images Using Aura Transformation

Abstract: An important and vital form to extract important and critical information from medical images is image processing. Distortion during image acquisition may lead to wrong diagnosis of the disease and thus may lead to negative conditions for the patient. So to overcome this problem the concept of aura transformation is used. In this, a structuring element is predefined and then it is compared to the complete pixel distribution relatively. This relativity is measured in terms of aura measure. This shows promising results and could be implemented on practical medical imagery for enhanced performance.

Evaluation of multiple and multiscale morphological profiles on the classification of hyperspectral image

Abstract: Hyperspectral data sets with high spatial resolution have been widely used in the research of image classification. The methodology based on the mathematical morphology, which aims at extracting the structure of hyperspectral images, has been implemented. In this method, opening and closing morphological operation used in hyperspectral data in order to retain spatial information of objects. Morphological profiles are established based on opening and closing transforms with structure element of different size. The proper definition of structure elements is the key of extracting morphological features for the image classification. Which kind of structural element is better for image classification. Can be discussed the classification results by setting different structural element to extract morphological features. In the experiments, we have defined four types of structure element to extract spatial features. Later on, the features are fed into a support vector machine (SVM) classifier respectively. The influence of different types of structure elements is judged by the classification accuracy. The experiment results illustrates disk shape of structural element is superior to diamond shape of structural element and the structural elements of large radius is better than the structural elements of small radius.

Authentication of classes of tulsi leaf for the extraction of medicinal qualities using image processing technique

Abstract: Leaf plays a major role in plant species. There are certain leaves which have medicinal qualities. Identification of leaf with look-alike is becoming a major task in day to day life. In order to overcome that computer vision technique is used which includes image processing algorithm. In this technique the features and texture of the leaf are extracted and the closest match is taken and identified to which class it belongs to. This paper deals with the algorithm of morphological processing to which the signature parameter is considered as the vein. Morphological processing includes structuring element which is a process of dilation and erosion. Authenticating an image with its signature parameter will be the most efficient method of identification to give highest accuracy than other methods.