Categorical Classification and Deletion of Spam Images on Smartphones Using Image Processing and Machine Learning

Arjit Sachdeva, R. Kapoor, Amit Sharma, Akshit Mishra
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引用次数: 3

Abstract

We regularly use communication apps like Facebook and WhatsApp on our smartphones, and the exchange of media, particularly images, has grown at an exponential rate. There are over 3 billion images shared every day on Whatsapp alone. In such a scenario, the management of images on a mobile device has become highly inefficient, and this leads to problems like low storage, manual deletion of images, disorganization etc. In this paper, we present a solution to tackle these issues by automatically classifying every image on a smartphone into a set of predefined categories, thereby segregating spam images from them, allowing the user to delete them seamlessly.
使用图像处理和机器学习在智能手机上分类和删除垃圾图像
我们经常在智能手机上使用Facebook和WhatsApp等通信应用程序,媒体的交换,尤其是图像的交换,以指数级的速度增长。仅在Whatsapp上,每天就有超过30亿张图片被分享。在这种情况下,移动设备上的图像管理变得非常低效,这导致了诸如低存储、手动删除图像、混乱等问题。在本文中,我们提出了一个解决这些问题的解决方案,通过自动将智能手机上的每张图像分类到一组预定义的类别中,从而将垃圾图像从它们中分离出来,允许用户无缝地删除它们。
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