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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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Journal ArticleDOI
01 Jun 1997
TL;DR: It is found that IIMD is superior to granulometric moments and MRRISAR in rotated texture classification and may also perform better than multichannel Gabor filters by employing many different kinds of structuring elements.
Abstract: An improved algorithm based on iterative morphological decomposition (IMD) proposed by Wang et al. (1993) is described. The proposed algorithm requires less computation than the original IMD algorithm. The improved iterative morphological decomposition (IIMD) is compared with granulometric moments, multiresolution rotation-invariant SAR (MRRISAR) models and multichannel Gabor filters. It is found that IIMD is superior to granulometric moments and MRRISAR in rotated texture classification. IIMD may also perform better than multichannel Gabor filters by employing many different kinds of structuring elements. In the study, three kinds of pseudo rotation-invariant structuring elements, namely the disc, octagon and square, as well as a line structuring element are tested. Since the line structuring element is rotation-variant in nature, the image is rotated to different orientations of equal angular separation to find a set of primitive features. A Fourier transform is then applied to convert these features to rotation-invariant. An accuracy rate as high as 96% is achieved in classifying 30 classes of textured images in the experiment. It is also demonstrated that using both the normalised variance and the mean can give better classification accuracy rate than using both the variance and the mean when classified by simplified Bayes or Mahalanobis distance measure.

45 citations

Journal ArticleDOI
TL;DR: In this article, a new morphology-based homomorphic filtering technique for feature enhancement in medical images is proposed based on decomposing an image into morphological subbands and applying differential evolution algorithm to find an optimal gain and structuring element for each subband.
Abstract: In this paper, we present a new morphology-based homomorphic filtering technique for feature enhancement in medical images. The proposed method is based on decomposing an image into morphological subbands. The homomorphic filtering is performed using the morphological subbands. The differential evolution algorithm is applied to find an optimal gain and structuring element for each subband. Simulations show that the proposed filter improves the contrast of the features in medical images.

45 citations

Journal ArticleDOI
TL;DR: In this article, a new double-dot structuring element is constructed for multi-scale mathematical morphology (MM) to extract features from one-dimensional signals, and a correlation analysis gives the final identification result by utilizing information over a whole pattern spectrum.
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 ...

45 citations

Journal ArticleDOI
TL;DR: A new class of top-hat transformation through structuring element construction and operation reorganization based on the property of the infrared small target image can greatly improve the performance of small target enhancement.
Abstract: To improve the performance of a top-hat transformation for infrared small target enhancement, a new class of top-hat transformation through structuring element construction and operation reorganization is proposed. The structuring element construction and operation reorganization are based on the property of the infrared small target image and thus can greatly improve the performance of small target enhancement. Experimental results verified that it was very efficient.

45 citations

Journal ArticleDOI
P. Sun1, Qinghua Wu1, A.M. Weindling, A. Finkelstein, K. Ibrahim 
TL;DR: An improved morphological approach to remove baseline wander from neonatal electrocardiogram (ECG) signals, with particular emphasis on preserving the ST segment of the original signal.
Abstract: This paper describes an improved morphological approach to remove baseline wander from neonatal electrocardiogram (ECG) signals, with particular emphasis on preserving the ST segment of the original signal. The algorithm consists of two stages of morphological processing. First, the QRS complex and impulsive noise component due to skeletal muscle contractions etc., are detected and removed from the input signal. Second, the corrected QT interval (QTc) and RR interval are used to determine a structuring element. With this structuring element, the same morphological operation as in the first stage is then applied to the QRS-removed signal to obtain and remove the baseline wander. The performance of the algorithm is evaluated with simulated and real ECGs. Compared with an existing morphological method, there is a substantial improvement, especially in reducing distortion of the baseline waveform within the PR and QT intervals.

44 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202214
202112
202019
201929
201824