Face Detection using Haar Cascades to Filter Selfie Face Image on Instagram
Adri Priadana, Muhammad Habibi · 2019
Instagram is one of the fastest growing social media in recent years. Instagram is a popular social media that is used to share images. An image search on Instagram can use a particular keyword or often called hashtag. There are no rules in giving hashtag when users upload pictures. It makes the hashtag given sometimes not related to the uploaded image. There are images whose contents are dominated by selfie face. It causes the background image or location of an image not to be conveyed entirely. The purpose of this study is to filter selfie face images on search results based on hashtags on Instagram by combining web data extraction technique and human face detection technique using the Haar Cascade method. The experiment was carried out by determining several hashtags as the basis for image search on Instagram. Experimental results show that the applied method produces an accuracy value of 71.48% for detecting human faces. According to the result of human face detection, Haar Cascade method can filter selfie face images that have an accuracy value of 64,6%. We use this assumption because basically, selfie face images contain a human face.