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[IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Hybrid Change Detection Based on ISFA for High-Resolution Imagery
摘要： Hybrid change detection (HCD) for high-resolution imagery usually adopt decision-level method and rely on artificial design. To address this issue, we propose a novel feature-level fusion strategy for HCD based on iterative slow feature analysis (ISFA). First, objects are obtained by multi-resolution segmentation of bi-temporal images respectively, and corresponding feature sets are constructed through stacking pixel- and object-level spectral features. Then, slow feature analysis (SFA) is used for transforming the feature sets into a new feature space at the first time. And iteration method with variable weights is introduced to get the last slow feature fusion map, where the changed pixels and unchanged pixels can be separated more easily. At last, K-means cluster is adopted to separate changed area and unchanged area automatically and generate final change result. Experiments were conducted on bi-temporal multi-spectral images, demonstrating the good performance of the proposed approach.
关键词： hybrid change detection,multi-scale fusion,feature-level fusion,iterative slow feature analysis
更新于2025-09-23 15:22:29
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Feature-Level Fusion of Landsat 8 Data and SAR Texture Images for Urban Land Cover Classification
摘要： Each of the urban land cover types has unique thermal pattern. Therefore, thermal remote sensing can be used over urban areas for indicating temperature differences and comparing the relationships between urban surface temperatures and land cover types. On the other hand, synthetic-aperture radar (SAR) sensors are playing an increasingly important role in land cover classi?cation due to their ability to operate day and night through cloud cover, and capturing the structure and dielectric properties of the earth surface materials. In this research, a feature-level fusion of SAR image and all bands (optical and thermal) of Landsat 8 data is proposed in order to modify the accuracy of urban land cover classi?cation. In the proposed object-based image analysis algorithm, segmented regions of both Landsat 8 and SAR images are utilized for performing knowledge-based classi?cation based on the land surface temperatures, spectral relationships between thermal and optical bands, and SAR texture features measured in the gray-level co-occurrence matrix space. The evaluated results showed the improvements of about 2.48 and 0.06 for overall accuracy and kappa after performing feature-level fusion on Landsat 8 and SAR data.
关键词： Thermal remote sensing,SAR data,Object-based image analysis,Textural features,Feature-level fusion
更新于2025-09-23 15:21:21
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An Innovative Approach for Person Identification by Detection and Extraction of Optic Disc from Retina and Concha from Ear
摘要： Person identification based on unimodal biometric system suffers from intra class similarity, non universality, distinctiveness and spoof attacks. To alleviate the problem faced in unimodal biometric system biometric traits are combined in multimodal biometric system. In this study a new approach, to improve the recognition rate, reduces computational complexity and storage space is presented. Distinct method of person identification using detection and extraction of optic disc from retina and concha from ear is carried out Region Of Interest (ROI) locator which is proposed here automatically detects the optic disc either from right or left eye and extracts it. Feature level fusion of optic disc and concha is done for recognition of a person. The method is tested with ROI locator and without ROI locator on publicly available databases and the experimental result shows that our multimodal biometric system outperforms with ROI locator than Without ROI locator. Matching Rate (MR) of 95 to 100% and Equal Error Rate (EER) of less than 10% is achieved with this system. The new approach was tested for unimodal system with ROI locator and was able to achieve 100% Matching Rate.
关键词： Optic Disc,Feature Level Fusion,Multimodal Biometric System,Unimodal Biometric System,Concha
更新于2025-09-04 15:30:14