Abstract:
"
Photography is one of the most trending domains in the modern world where anyone
can be a part of it. Capturing an image with a bit of creativity simply showcases the
passion towards photography and it is the art of capturing light using a camera to
produce an image using a digital sensor. Images can be captured using digital cameras
as well as mobile phone cameras where each camera produces equal amounts of quality
nowadays.
Exposure plays a huge role in photography where it determines the lighting of an image.
Exposure triangle which consists of ISO, Shutter speed and Aperture is known as the
three pillars of photography which impact the quality of an image. Photographers tend
to use both manual and auto modes to shoot images where quality of the image is
checked using their own naked eyes. Manual settings are preferred more by
photographers where it gives more control over the camera to capture quality images
and gives a chance to be more creative.
Through research it was identified that amateur photographers take more time to learn
and properly use manual camera settings when shooting images and also unable to
determine the quality of the captured image. This project would provide a solution for
this addressed matter by developing a mobile application to capture images and assess
image quality in real time and then recommend manual camera settings according to
the image quality. Enhancing and showcasing meta data of the captured image would
be features of this application. Image processing, image classification and
convolutional neural networks were the technologies used in this system development.
The author believes that this solution would be beneficial for amateur photographers to
learn more about photography and take control over the cameras through the success of
this project"
