DARK ROOM - An Algorithmic Approach to Identify Blurred Images in Bulk Image Using Computational Intelligence

Abstract

With the invention Digital Single Lens Reflex (DSLR) cameras, Computer-based electronic digital photography revolutionised the photography industry with digital images. Accordingly, the images quality also has improved compared to previous years. Similarly, with the development of cameras and its user-friendliness has become closer to individuals nowadays. In current, with all these revolutionised changes the competition also has arisen aggressively. This competition is mainly based on the picture quality and the perfectness of the image. Hence, editors occupy a lot of time and effort to achieve the perfection in the pictures. The most common challenge faced by photographers and photo editors is how to select the best images from a large number of pictures. Furthermore, time and effort that the photographer or editor spends are considerably high due to reasons like, photographer or photo editor should go through all the photographs to identify what are the perfect images and photographer or editor have to identify blurred photographs by checking one by one. A survey was conducted among the photographers in Sri Lanka and it was that the existing applications do not identify the low-quality images and do not satisfy all of the industry requirements. Hence, the existing algorithms, image processes methods, and other approaches had to be critically reviewed to identify the gap wholly.