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:
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.
Method:
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.
Image
Segmentation:
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:
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.
