Object Localization and Tracking

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Image processing has provided ease to many of the applications where the task could have been very difficult with some other techniques. One such example is the case where the impact of water stream is to be analyzed; now there are various possible ways in which one can study the impact of running water stream. The principles of fluid mechanics in this case can be simplified if an object moving in the stream is taken into account and its motion is analyzed.

In order to understand the motion exhibited by the object moving under the influence of running stream it becomes mandatory to continuously track the object in the stream and this is where Image Processing comes into role.

The object moving in the running water stream due to the force exerted by the stream can be tracked utilizing the principles of image processing. One could employ one or more of the following available approaches to do so:

  • Gaussian smoothing
  • Blob Detection
  • Color Tracking

Gaussian smoothing is the result of blurring an image by a Gaussian function. It is a widely used effect in graphics software, typically to reduce image noise and reduce detail. The visual effect of this blurring technique is a smooth blur resembling that of viewing the image through a translucent screen,

In computer vision, blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to surrounding regions. In other words, a blob is a region of an image in which some properties are constant or approximately constant; all the points in a blob can be considered in some sense to be similar to each other.

The easiest way among these is to detect and segment an object from an image is the color based methods. The object and the background should have a significant color difference in order to successfully segment objects using color based methods.

Object tracking using color tracking was an optimum solution in the above mentioned scenario, the object to be tracked was distinguished from its background on the basis of its color and successful tracking was done.

The challenge here was to track the cube in the running water steam. In this, precise tracking information was required. This was a part of research project where the objective was to study the impact of water stream.

Merely finding out various solutions for a given problem was not the only prime consideration but choosing an optimum solution is what we strive for.