Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when deal...Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.展开更多
This paper puts forward an effective, specific algorithm for edge detection. Based on multi-structure elements of gray mathematics morphology, in the light of difference between noise and edge shape of RS images, the ...This paper puts forward an effective, specific algorithm for edge detection. Based on multi-structure elements of gray mathematics morphology, in the light of difference between noise and edge shape of RS images, the paper establishes multi-structure elements to detect edge by utilizing the grey form transformation principle. Compared with some classical edge detection operators,such as Sobel Edge Detection Operator, LOG Edge Detection Operator, and Canny Edge Detection Operator, the experiment indicates that this new algorithm possesses very good edge detection ability, which can detect edges more effectively, but its noise-resisting ability is relatively low. Because of the bigger noise of remote sensing image, the authors probe into putting forward other edge detection method based on combination of wavelet directivity checkout technology and small-scale Mathematical Morphology finally. So, position at the edge can be accurately located, the noise can be inhibited to a certain extent and the effect of edge detection is obvious.展开更多
By using image recognition technology, the underground bin level can be detdcted. The bin image is noised by vibration, atomy, backgroun and so on. The image restoration and image mathematical morphology were used bas...By using image recognition technology, the underground bin level can be detdcted. The bin image is noised by vibration, atomy, backgroun and so on. The image restoration and image mathematical morphology were used based on neural network. A modified Hopfield network was presented for image restoration. The greed algorithm with n-simultaneous updates and apartially asynchronous algorithm were combined, im- proving convergence and avoiding synchronization penalties. Mathematical morphology was widely applicated in digital image processing. The basic idea of mathematical mor- phology is to use construction element measure image morphology for solving under- stand problem. Presented advanced Cellular neural network that forms MMCNN equa- tion to be suit for mathematical morphology filter. It gave the theory of MMCNN dynamic extent and stable state. It was evidenced that arrived mathematical morphology filter through steady of dynamic precess in definite condition. The results of implementation were applied in detecting undergroug bin level.展开更多
An adaptive algorithm for removing false ridges, bridges and filling gaps in binary fingerprint images based on morphological operations is presented. A novel procedure for structuring elements design based on the spe...An adaptive algorithm for removing false ridges, bridges and filling gaps in binary fingerprint images based on morphological operations is presented. A novel procedure for structuring elements design based on the specific fingerprint characteristic is described. Using the images from FVC2000 database, we have compared our method proposed here with the approach proposed by other ones. The Experimental results have demonstrated the efficiency of our method.展开更多
The structure and morphology of the hepatic vessels and their relationship between tumors and liver segments are major interests to surgeons for liver surgical planning. In case of living donor liver transplantation (...The structure and morphology of the hepatic vessels and their relationship between tumors and liver segments are major interests to surgeons for liver surgical planning. In case of living donor liver transplantation (LDLT), the most important step in determining donor suitability is an accurate assessment of the liver volume available for transplantation. In addition, the mutual principles of the procedures include dissection in the appropriate anatomic plane without portal occlusion, minimization of blood loss, and avoidance of injury to the remaining liver. It is essential first step to identify and evaluate the major hepatic vascular structure for liver surgical planning. In this paper, the threshold was determined to segment the liver region automatically based on the distribution ratio of intensity value;and the hepatic vessels were extracted with mathematical morphology transformation, which called hit operation, that is slightly modified version of hit-and-miss operation on contrast enhanced CT image sequence. We identified the vein using the preserved voxel connectivity between two consecutive transverse image sequences, followed by resection into right lobe including right hepatic vein, middle hepatic vein branches andleft lobe including left hepatic vein. An automated hepatic vessel segmentation scheme is recommended for liver surgical planning such as tumor resection and transplantation. These vessel extraction method combined with liver region segmentation technique could be applicable to extract tree-like organ structures such as carotid, renal, coronary artery, and airway path from various medical imaging modalities.展开更多
Working conditions of rolling bearings of wind turbine generators are complicated, and their vibration signals often show non-linear and non-stationary characteristics. In order to improve the efficiency of feature ex...Working conditions of rolling bearings of wind turbine generators are complicated, and their vibration signals often show non-linear and non-stationary characteristics. In order to improve the efficiency of feature extraction of wind turbine rolling bearings and to strengthen the feature information, a new structural element and an adaptive algorithm based on the peak energy are proposed,which are combined with spectral correlation analysis to form a fault diagnosis algorithm for wind turbine rolling bearings. The proposed method firstly addresses the problem of impulsive signal omissions that are prone to occur in the process of fault feature extraction of traditional structural elements and proposes a "W" structural element to capture more characteristic information. Then, the proposed method selects the scale of multi-scale mathematical morphology, aiming at the problem of multi-scale mathematical morphology scale selection and structural element expansion law. An adaptive algorithm based on peak energy is proposed to carry out morphological scale selection and structural element expansion by improving the computing efficiency and enhancing the feature extraction effect.Finally, the proposed method performs spectral correlation analysis in the frequency domain for an unknown signal of the extracted feature and identifies the fault based on the correlation coefficient. The method is verified by numerical examples using experimental rig bearing data and actual wind field acquisition data and compared with traditional triangular and flat structural elements. The experimental results show that the new structural elements can more effectively extract the pulses in the signal and reduce noise interference,and the fault-diagnosis algorithm can accurately identify the fault category and improve the reliability of the results.展开更多
Shoreline extraction is fundamental and inevitable for several studies.Ascertaining the precise spatial location of the shoreline is crucial.Recently,the need for using remote sensing data to accomplish the complex ta...Shoreline extraction is fundamental and inevitable for several studies.Ascertaining the precise spatial location of the shoreline is crucial.Recently,the need for using remote sensing data to accomplish the complex task of automatic extraction of features,such as shoreline,has considerably increased.Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating.Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps.Here,we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries.The salient features of this work are the preservation of actual size and shape of the shorelines,run-time structuring element definition,semi-automation,faster processing,and single band adaptability.The proposed approach is tested with various sensor-driven images with low to high resolutions.Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach.The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments.展开更多
文摘Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.
基金Foundation item: Under the auspices of the National Natural Science Foundation of China (No. 49971055
文摘This paper puts forward an effective, specific algorithm for edge detection. Based on multi-structure elements of gray mathematics morphology, in the light of difference between noise and edge shape of RS images, the paper establishes multi-structure elements to detect edge by utilizing the grey form transformation principle. Compared with some classical edge detection operators,such as Sobel Edge Detection Operator, LOG Edge Detection Operator, and Canny Edge Detection Operator, the experiment indicates that this new algorithm possesses very good edge detection ability, which can detect edges more effectively, but its noise-resisting ability is relatively low. Because of the bigger noise of remote sensing image, the authors probe into putting forward other edge detection method based on combination of wavelet directivity checkout technology and small-scale Mathematical Morphology finally. So, position at the edge can be accurately located, the noise can be inhibited to a certain extent and the effect of edge detection is obvious.
文摘By using image recognition technology, the underground bin level can be detdcted. The bin image is noised by vibration, atomy, backgroun and so on. The image restoration and image mathematical morphology were used based on neural network. A modified Hopfield network was presented for image restoration. The greed algorithm with n-simultaneous updates and apartially asynchronous algorithm were combined, im- proving convergence and avoiding synchronization penalties. Mathematical morphology was widely applicated in digital image processing. The basic idea of mathematical mor- phology is to use construction element measure image morphology for solving under- stand problem. Presented advanced Cellular neural network that forms MMCNN equa- tion to be suit for mathematical morphology filter. It gave the theory of MMCNN dynamic extent and stable state. It was evidenced that arrived mathematical morphology filter through steady of dynamic precess in definite condition. The results of implementation were applied in detecting undergroug bin level.
基金supported by the National Nature Science Foundation of China under Grant No.60605007J
文摘An adaptive algorithm for removing false ridges, bridges and filling gaps in binary fingerprint images based on morphological operations is presented. A novel procedure for structuring elements design based on the specific fingerprint characteristic is described. Using the images from FVC2000 database, we have compared our method proposed here with the approach proposed by other ones. The Experimental results have demonstrated the efficiency of our method.
文摘The structure and morphology of the hepatic vessels and their relationship between tumors and liver segments are major interests to surgeons for liver surgical planning. In case of living donor liver transplantation (LDLT), the most important step in determining donor suitability is an accurate assessment of the liver volume available for transplantation. In addition, the mutual principles of the procedures include dissection in the appropriate anatomic plane without portal occlusion, minimization of blood loss, and avoidance of injury to the remaining liver. It is essential first step to identify and evaluate the major hepatic vascular structure for liver surgical planning. In this paper, the threshold was determined to segment the liver region automatically based on the distribution ratio of intensity value;and the hepatic vessels were extracted with mathematical morphology transformation, which called hit operation, that is slightly modified version of hit-and-miss operation on contrast enhanced CT image sequence. We identified the vein using the preserved voxel connectivity between two consecutive transverse image sequences, followed by resection into right lobe including right hepatic vein, middle hepatic vein branches andleft lobe including left hepatic vein. An automated hepatic vessel segmentation scheme is recommended for liver surgical planning such as tumor resection and transplantation. These vessel extraction method combined with liver region segmentation technique could be applicable to extract tree-like organ structures such as carotid, renal, coronary artery, and airway path from various medical imaging modalities.
基金supported by National Natural Science Foundation of China (No. 61763037)Inner Mongolia Autonomous Region Natural Science Foundation of China(No. 2019LH06007)Science and Technology Plan Project of Inner Mongolia (No. 2019,2020GG028)。
文摘Working conditions of rolling bearings of wind turbine generators are complicated, and their vibration signals often show non-linear and non-stationary characteristics. In order to improve the efficiency of feature extraction of wind turbine rolling bearings and to strengthen the feature information, a new structural element and an adaptive algorithm based on the peak energy are proposed,which are combined with spectral correlation analysis to form a fault diagnosis algorithm for wind turbine rolling bearings. The proposed method firstly addresses the problem of impulsive signal omissions that are prone to occur in the process of fault feature extraction of traditional structural elements and proposes a "W" structural element to capture more characteristic information. Then, the proposed method selects the scale of multi-scale mathematical morphology, aiming at the problem of multi-scale mathematical morphology scale selection and structural element expansion law. An adaptive algorithm based on peak energy is proposed to carry out morphological scale selection and structural element expansion by improving the computing efficiency and enhancing the feature extraction effect.Finally, the proposed method performs spectral correlation analysis in the frequency domain for an unknown signal of the extracted feature and identifies the fault based on the correlation coefficient. The method is verified by numerical examples using experimental rig bearing data and actual wind field acquisition data and compared with traditional triangular and flat structural elements. The experimental results show that the new structural elements can more effectively extract the pulses in the signal and reduce noise interference,and the fault-diagnosis algorithm can accurately identify the fault category and improve the reliability of the results.
文摘Shoreline extraction is fundamental and inevitable for several studies.Ascertaining the precise spatial location of the shoreline is crucial.Recently,the need for using remote sensing data to accomplish the complex task of automatic extraction of features,such as shoreline,has considerably increased.Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating.Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps.Here,we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries.The salient features of this work are the preservation of actual size and shape of the shorelines,run-time structuring element definition,semi-automation,faster processing,and single band adaptability.The proposed approach is tested with various sensor-driven images with low to high resolutions.Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach.The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments.