Aimed at low contrast effect on fabric detection,a method based on bilateral filter and frangi filter is proposed. Firstly,in order to reduce the influence of fabric background texture information on the detection res...Aimed at low contrast effect on fabric detection,a method based on bilateral filter and frangi filter is proposed. Firstly,in order to reduce the influence of fabric background texture information on the detection results,bilateral filter is used to deal with the fabric image. Then frangi filter is used to filter the fabric image after bilateral filtering to enhance the fabric defect area information. Finally,a maximum entropy method is implemented on the fabric image after frangi filtering to separate the defected area. Experimental results show that the proposed method can effectively detect defects.展开更多
Diabetes is a significant issue in the medical field. The detection and identification of the human eye diseases caused by excessive blood sugar levels in diabetes mellitus are important. The main objective of this st...Diabetes is a significant issue in the medical field. The detection and identification of the human eye diseases caused by excessive blood sugar levels in diabetes mellitus are important. The main objective of this study is to propose a viable solution for diagnosis using fundus images. This study presents a stage by stage implementation methodology. The original fundus image is first preprocessed, then the blood vessels are segmented, and finally the features are extracted and classified. This work uses an effective way to introduce a meta-heuristic algorithm. Blood Vessel Segmentation(BVS) is vital in DR(Diabetic Retinopathy) detection;hence, this research proposes a Firefly-Optimized Frangi based Filter(FOFF). Categorizing the disease is the last procedure. The classifier K-Nearest Neighbour(KNN) has an accuracy of 91.62%, while the SVM does well with an accuracy score of 95.54%.展开更多
文摘Aimed at low contrast effect on fabric detection,a method based on bilateral filter and frangi filter is proposed. Firstly,in order to reduce the influence of fabric background texture information on the detection results,bilateral filter is used to deal with the fabric image. Then frangi filter is used to filter the fabric image after bilateral filtering to enhance the fabric defect area information. Finally,a maximum entropy method is implemented on the fabric image after frangi filtering to separate the defected area. Experimental results show that the proposed method can effectively detect defects.
文摘Diabetes is a significant issue in the medical field. The detection and identification of the human eye diseases caused by excessive blood sugar levels in diabetes mellitus are important. The main objective of this study is to propose a viable solution for diagnosis using fundus images. This study presents a stage by stage implementation methodology. The original fundus image is first preprocessed, then the blood vessels are segmented, and finally the features are extracted and classified. This work uses an effective way to introduce a meta-heuristic algorithm. Blood Vessel Segmentation(BVS) is vital in DR(Diabetic Retinopathy) detection;hence, this research proposes a Firefly-Optimized Frangi based Filter(FOFF). Categorizing the disease is the last procedure. The classifier K-Nearest Neighbour(KNN) has an accuracy of 91.62%, while the SVM does well with an accuracy score of 95.54%.
