Mining and Clustering the Feature Similarities of Images on Smart Phone

M. Samiya, S. Sharmiladevi, K. Surya, R. Sudha
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Abstract

With the fame of visual sensor on smart phone devices, ( i.e. camera) it becomes a habit for many people to capture photos everyday and everywhere. This led to the rapid developing of more personal images and becomes a nuisance to the users in storing and organizing them, which had not been used before. Lu c k i l y , cloud storage provided a comprehensive solution at the right moment, and it facilitates the synchronization and sharing of images acquired. However, organizing this bulk number of personal images is still a tedious and difficult task. Common needs in photo organization may involve tagging, destroying replicated or same images, and collecting photos into albums. In our proposed system, we target to provide a features similarity images, face detection and recognition, avoid redundancy on smart mobile application which makes use of existing sensors and related technologies to help users to manage replicate or same images more effectively. By sharpening the power of cloud computing for SSIM algorithm, our system significantly reduce the time spent on managing photos in a neat and simple way which reduce user stress and increase user experience. KeywordsPhoto organization, Image similarity, Cloud storage, Mobile application, Redundancy avoidance.
智能手机图像特征相似性的挖掘与聚类
随着智能手机上的视觉传感器(即相机)的普及,许多人每天随地拍照已经成为一种习惯。这导致了更多的个人图像的快速发展,并成为用户在存储和组织他们之前没有使用过的麻烦。然而,云存储在合适的时机提供了一个全面的解决方案,它促进了获取图像的同步和共享。然而,组织大量的个人图像仍然是一项乏味而困难的任务。照片组织的常见需求可能包括标记、销毁复制或相同的图像,以及将照片收集到相册中。在我们提出的系统中,我们的目标是提供一个特征相似的图像,人脸检测和识别,避免冗余的智能移动应用程序,利用现有的传感器和相关技术,帮助用户更有效地管理重复或相同的图像。通过增强SSIM算法的云计算能力,我们的系统大大减少了管理照片所花费的时间,以一种简洁的方式减少了用户的压力,增加了用户体验。关键词:照片组织,图像相似度,云存储,移动应用,冗余避免
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