Executive Summary : | The world is living virtually, leading to the creation of new life online. Creating connections with strangers and reaching out to them without hesitation is making a place for crimes to settle. Studies claim this culture has encouraged witty heads to cheat innocents and force them to send obscene images. This practice is also sometimes referred to as 'sexting,' which is commonly defined as sharing intimate images on social media chats. Adults also face this problem in the workplace, where one mistake can lead to sexual harassment cases and expensive lawsuits. It is often the case when an employee unknowingly stores or shares sensitive personal images circulating them in the organization's network, ruining not only the social lives but also the work life of their colleagues. It can also very well be some form of malware that spreads illicit images inside the organization and needs to be stopped immediately. Kids these days are obsessed about obtaining attention on social media. To get a huge number of followers, they try to engage the audience with unsuitable content that pollutes their minds. The aim is to build and implement a process to extrude obscene images from an image-capturing device. A method of integration and a feasible machine-learning model which can be integrated with image capturing device will be devised. It will detect obscene images clicked from a camera of the image capturing device at the client side itself, i.e., no internet is required for the detection of obscene images. It will run in the background of the image-capturing device and will prevent inappropriate images from saving, sharing and will automatically delete the obscene images from the image storage of the image capturing device, just after they are being clicked. It will keep or save the images only if they belong to the safe category. |