A new method, triplet circular Hough transform, is proposed for circle detection in image processing and pattern recognition. In the method, a curve in an image is first detected. Next, a sequence of three points on t...A new method, triplet circular Hough transform, is proposed for circle detection in image processing and pattern recognition. In the method, a curve in an image is first detected. Next, a sequence of three points on the curve are selected, a sequence of parameters (a,b,r) corresponding to the three points are calculated by solving the circle equation of the curve, and two 2-D accumulators A(a,b) and R(a,b) are accumulated with 1 and r, respectively. Then the parameters {(a, b, r)} of the circles fitting the curve are determined from A(a,b) and R(a,b) by searching for the local maximum over A(a,b). Because no computation loops over center (a, 6) and/or radius r are needed, the method is faster than the basic and directional gradient methods. It needs also much smaller memory for accumulation.展开更多
In order to solve the problem of internal defect detection in industry, an intelligent detection method for workpiece defect based on industrial computed tomography (CT) images is proposed. The industrial CT slice ima...In order to solve the problem of internal defect detection in industry, an intelligent detection method for workpiece defect based on industrial computed tomography (CT) images is proposed. The industrial CT slice image is preprocessed first with the combination of adaptive median filtering and adaptive weighted average filtering by analyzing the characteristics of the industrial CT slice images. Then an image segmentation algorithm based on gray change rate is used to segment low contrast information in industrial CT images, and the feature of workpiece defect is extracted by using Hu invariant moment. On this basis, the radial basis function (RBF) neural network model is established and the firefly algorithm is used for optimization, and the intelligent identification of the internal defects of the workpiece is completed. Simulation results show that this method can effectively improve the accuracy of defect identification and provide a theoretical basis for the detection of internal defects in industry.展开更多
Image processing plays an important role in engineering treatment. The authors mainly introduced the feature recognition of borehole image process based on Ant Colony Algorithm (ACA). The most important geological str...Image processing plays an important role in engineering treatment. The authors mainly introduced the feature recognition of borehole image process based on Ant Colony Algorithm (ACA). The most important geological structure-fracture on the borehole image was identified, and quantitative parameters were obtained by HOUGH transform. Several case studies show that the method is feasible.展开更多
Intravascular ultrasound (IVUS) is a new technology for the diagnosis of coronary artery disease, and for the support of coronary intervention. IVUS image segmentation often encounters difficulties when plaque and aco...Intravascular ultrasound (IVUS) is a new technology for the diagnosis of coronary artery disease, and for the support of coronary intervention. IVUS image segmentation often encounters difficulties when plaque and acoustic shadow are present A novel approach for hard plaque recognition and media-adventitia border detection of IVUS images is presented in this paper. The IVUS images were first enhanced by a spatial-frequency domain filter that was constructed by the directional filter and histogram equalization. Then, the hard plaque was recognized based on the intensity variation within different regions that were obtained using the k-means algorithm. In the next step, a cost matrix representing the probability of the media-adventitia border was generated by combining image gradient, plaque location and image intensity. A heuristic graph-searching was applied to find the media-adventitia border from the cost matrix.Experiment results showed that the accuracy of hard plaque recognition and media-adventitia border detection was 89.94% and 95.57%, respectively. In conclusion,using hard plaques recognition could improve media-adventitia border detection in IVUS images.展开更多
基金Supported by the National Natural Science Foundation of China(No.30070228)
文摘A new method, triplet circular Hough transform, is proposed for circle detection in image processing and pattern recognition. In the method, a curve in an image is first detected. Next, a sequence of three points on the curve are selected, a sequence of parameters (a,b,r) corresponding to the three points are calculated by solving the circle equation of the curve, and two 2-D accumulators A(a,b) and R(a,b) are accumulated with 1 and r, respectively. Then the parameters {(a, b, r)} of the circles fitting the curve are determined from A(a,b) and R(a,b) by searching for the local maximum over A(a,b). Because no computation loops over center (a, 6) and/or radius r are needed, the method is faster than the basic and directional gradient methods. It needs also much smaller memory for accumulation.
基金Science and Technology Plan Project of Lanzhou City(No.2014-2-7)
文摘In order to solve the problem of internal defect detection in industry, an intelligent detection method for workpiece defect based on industrial computed tomography (CT) images is proposed. The industrial CT slice image is preprocessed first with the combination of adaptive median filtering and adaptive weighted average filtering by analyzing the characteristics of the industrial CT slice images. Then an image segmentation algorithm based on gray change rate is used to segment low contrast information in industrial CT images, and the feature of workpiece defect is extracted by using Hu invariant moment. On this basis, the radial basis function (RBF) neural network model is established and the firefly algorithm is used for optimization, and the intelligent identification of the internal defects of the workpiece is completed. Simulation results show that this method can effectively improve the accuracy of defect identification and provide a theoretical basis for the detection of internal defects in industry.
文摘Image processing plays an important role in engineering treatment. The authors mainly introduced the feature recognition of borehole image process based on Ant Colony Algorithm (ACA). The most important geological structure-fracture on the borehole image was identified, and quantitative parameters were obtained by HOUGH transform. Several case studies show that the method is feasible.
文摘Intravascular ultrasound (IVUS) is a new technology for the diagnosis of coronary artery disease, and for the support of coronary intervention. IVUS image segmentation often encounters difficulties when plaque and acoustic shadow are present A novel approach for hard plaque recognition and media-adventitia border detection of IVUS images is presented in this paper. The IVUS images were first enhanced by a spatial-frequency domain filter that was constructed by the directional filter and histogram equalization. Then, the hard plaque was recognized based on the intensity variation within different regions that were obtained using the k-means algorithm. In the next step, a cost matrix representing the probability of the media-adventitia border was generated by combining image gradient, plaque location and image intensity. A heuristic graph-searching was applied to find the media-adventitia border from the cost matrix.Experiment results showed that the accuracy of hard plaque recognition and media-adventitia border detection was 89.94% and 95.57%, respectively. In conclusion,using hard plaques recognition could improve media-adventitia border detection in IVUS images.
