Study of Feature Apprehension Using Soft Computing Approaches

Study of Feature Apprehension Using Soft Computing Approaches

Deepika Dubey (Uttarakhand Technical University, India), Deepika Singh Kushwah (Jaypee University of Engineering and Technology, India) and Deepanshu Dubey (Indian Institute of Forest Management, India)
Copyright: © 2018 |Pages: 21
DOI: 10.4018/978-1-5225-3531-7.ch009


An image may be mist full for the one or may be nostalgic for the other. But for a researcher, each image is distinguished on the basis of its low-level features like color, shape, size. Other features like edges, corner/interesting points, blobs/region of interest, ridges, etc. can also be used for computation purpose. Using these features distinctions, an image can be processed for the purpose of enhancing the images having same features, matching, and shortlisting of similar images from a random available image database. This could be done using soft computing techniques like neural networks, fuzzy logic, and evolutionary computation methods. Neural networks can participate effectively in image processing in several ways.
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This is the starting of the virtual system in which we merge two different techniques Modares et al. (2013) to solve task smoothly and easily. In this section we are discussing about what feature detection is? And how it is helpful in computer vision. How the pictorial representation of data is being calculated and how a computer process an image. In overview of this chapter you will find out you will final a general introduction about the facts and knowledge about the topic. There is no references used in this section all the references used in the mid and end of it.

The Human Vision

A computer vision is a techniques in which system process an image which is captured by camera like electronic camera, digital camera or by using mobile phone camera, which is same compared by the human vision. The whole working is inspired by human vision working like and image captured by an eye and send it to the brain and with the help of brain neuron we will process that image for further applications. This is very interesting topic on which researcher and scientist are working. Liu et al. (2014) .Now a day it is used and form a commercial fortune. There are so many vision system which check software part as well as mechanical parts to fetch the features.

Main use of this type of technologies are forensic studies and in biometric using human vision as well as computer vision which included face recognition, finger print recognition and handwriting recognition. These study also helpful in field of biologist and physiologist who compare it with human vision system that how human vision system work and how the whole processing is helpful to recognize objects. Haykin (1994) An image is selected after selection of image set of points called feature (pixel) excluded with the help of it we analysis the shape, feature color and texture of the image. These all analysis is done with the use of human vision system.

Human vision is a knowledgeable system that aware and take action on visual boost. Rani et al. (2013) & Wang et al. (2015). Computer and human vision work as same or we can say that the computer vision is inspired from human vision system. The purpose of both the system action on the spatial data. Function of both the system are same, we cannot distinguished the main difference is human vision system use human eye for input and computer vision uses the scanner or camera for an image as input after that the whole processing is same.

Neural System

Neural system is the processes which is done by the neurons present in the human brain. Artificially we are using the concept of ANN (Artificial Neural Network) Modares et al. (2013) .Neurons sends the neural signals provided by the eye which is depend on the wavelength of the object. Shojaei (2015) the weight factor is also consider that control response of particular regions. Weighting factor help in filtering of the features. More detail about neural system explained below in this chapter.


The neural signals are transmitted in the brain in two parts for further processing are associative cortex (link between the objects) and occipital cortex (pattern processing). The input is captured by the eyes Melingui et al. (2015) & Yan (2012) and forwarded it to the brain next processing is done by the brain with the help of biological neuron by sending neural signals by operating the brain. Human vision system uses edges, boundaries of the objects to achieve the tasks.

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