Extracting some useful information from images is considered as Computer Vision. These images can be of any form from Visual to Infrared to X-rays in the whole electromagnetic spectrum. The basic idea is to duplicate human visual perception in images to extract the same information.
Some major applications of Computer vision consists tasks including Object detection, Object tracking, segmentation, Image inpainting and 3d modelling from images.
A lot of research work is carried out all over the globe in all of the above mentioned fields. So in this article we are going to discuss some of the very interesting yet strange fields for new comers.
Image inpainting is a process to recover some useful information from deteriorated images or give some artistic look to images by removing unwanted objects still maintaining smooth background. Such a task is a daily part of human life as imagine a person at some distinct place or removing a particular object from a scene but in computers, this is trivial.
First a binary map is created on the basis of which part of the image is to be removed. Now that part of the image is filled in a manner to minimize energy. This is often done using a very simple operator called Laplacian operator. This is essentially second order derivative of image. Second order derivatives are used because its direction is similar to the direction of edges rather than perpendicular to it as in the case of first order derivative. Thus we find to minimize this function as this would perfectly reflect the second order derivative.
Segmentation is a process of image processing to segment out one or more objects from an image. The goal is to find out a boundary of pixels that can perfectly differentiate between two objects based on colour or shape or both. Applications for image segmentation includes Object detection, Face detection and in medical imaging. Tumour detection, Surgery planning and diagnosis of anatomical structures are some of the major applications of segmentation in medical imaging.
Motion analysis is in the simplest case to find out a moving object from a sequence of images. This work can be extended to find the direction of movement, velocity and displacement calculation and object tracking. The basic idea is find out a static region (background) and a moving region with substantial displacement. One very popular method for this is finding the Optical flow. Motion analysis is extremely important in Surveillance and video object tracking. Tracking with a moving camera increases the complexity a lot due to the relative motion between camera and the object. Tracking with multiple cameras with overlapping or non-overlapping regions are current research issues in Object tracking.