- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2017 International Conference on Computational Science and Computational Intelligence (CSCI) - Las Vegas, NV, USA (2017.12.14-2017.12.16)] 2017 International Conference on Computational Science and Computational Intelligence (CSCI) - Estimation of Illumination Map from Dermoscopy Images for Extracting Differential Structures Using Gabor Local Mesh Patterns
摘要： Melanoma is the most deadly form of skin cancer and its incidence rate is significantly increasing. The design of an assisted diagnosis system for the detection of melanoma is a challenging task involving various steps related to computer vision. Researchers have concluded that the accurate identification of melanoma requires robust preprocessing steps on dermoscopy images including hair removal, illumination correction etc., that can help in a better detection of melanoma. In this paper, we propose a novel illumination correction algorithm followed by robust feature extraction from dermoscopy images, leading to a better identification of cancer. Illumination correction is based on statistical estimation of illumination content in the images, followed by the extraction of differential structures using a combination of Gabor filtering followed by extracting local mesh patterns, which exhibit physiological significance based on various clinical rules for detecting melanoma. Our experiments show that the proposed technique outperforms all the other methods that have been considered in this paper.
关键词： Texture analysis,Optimization,Pattern recognition,Gabor filters,Melanoma
更新于2025-09-23 15:22:29
-
Robust visible-infrared image matching by exploiting dominant edge orientations
摘要： Finding the correspondences between visible and infrared images is a challenging task due to the image spectral inconsistency which leads to large differences of gradient distributions between these images. To alleviate this problem, we propose a novel feature descriptor for visible and infrared image matching based on Log-Gabor filters. The descriptor employs multi-orientation and multi-scale Log-Gabor filters to encode the edge information statistically. Furthermore, the descriptor provides rotation invariance by estimating the dominant orientation which is based on accumulated edge orientations. The experimental results demonstrate the effectiveness of the proposed rotation invariant descriptor and the better performance for matching visible and longwave infrared images as compared with state-of-the-art descriptors.
关键词： Log-Gabor filters,rotation invariant descriptor,edge orientations,visible-infrared image matching
更新于2025-09-23 15:21:01
-
[IEEE 2018 10th International Conference on Communication Software and Networks (ICCSN) - Chengdu (2018.7.6-2018.7.9)] 2018 10th International Conference on Communication Software and Networks (ICCSN) - A New Sclera Segmentation and Vessels Extraction Method for Sclera Recognition
摘要： As a unique biometric trait, the research of sclera blood vessels have becomes active recently, because the sclera vessels can be captured under visible-wavelength light condition rather than near infrared light condition. However, the performance of sclera identification system degrades a lot due to unsatisfactory sclera segmentation and tedious extraction process. In this paper, we propose a novel sclera segmentation algorithm and an improved sclera vessels extraction method. The accurate and efficient sclera segmentation method is proposed based on improved OSTU algorithm. Besides, the vessels extraction method is put forward by adaptive histogram equalization method and Gabor filters. The experimental results on UBIRIS.v1 database prove that the proposed sclera vessels extraction algorithm performs well and the sclera segmentation method has an obvious improvement in terms of efficiency and accuracy over than other segmentation algorithms.
关键词： vessels extraction,local OSTU,Gabor filters,sclera segmentation
更新于2025-09-11 14:15:04
-
Analysis of gabor filter based features with PCA and GA for the detection of drusen in fundus images
摘要： Human eye can be affected by different types of diseases. Age-Related Macular Degeneration (AMD) is one of the such diseases, and it mainly occurs after 50 years of age. This disease is characterized by the occurrence of yellow spots called as Drusen. In this work, an automated method for the detection of drusen in Fundus image has been developed, and it has been tested on 70 images consisting of 30 normal images and 40 images with drusen. Performance of the Support Vector Machine (SVM) and K Nearest Neighbor (KNN) classifier has been evaluated using Data's reduction using Principle Component Analysis (PCA) and Data's selection using Genetic Algorithm (GA).Performance evaluation has been done in terms of accuracy, sensitivity, specificity, misclassification rate, positive predictive rate, negative predictive rate and Youden’s Index. The proposed method has achieved highest accuracy of 98.7% when data selection using Genetic Algorithm has been applied.
关键词： Genetic Algorithm,Principal Component Analysis,Support Vector Machine,Drusen,Gabor Filters
更新于2025-09-04 15:30:14