Edge Detection As an Effective Technique in Image Segmentation
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International Journal of Computer Science Trends and Technology (IJCST) – Volume 2 Issue 4, Nov-Dec 2014 RESEARCH ARTICLE OPEN ACCESS Edge Detection as an Effective Technique in Image Segmentation for Image Analysis Manjula KA Research Scholar Research Development Centre Bharathiar University Tamil Nadu – India ABSTRACT Digital Image processing is a technique making use of computer algorithms to perform specific operations on an image, to get an enhanced image or to extract some useful information from it. Image segmentation, which is an important phase in image processing, is the process of separation of an image into regions or categories, which correspond to different objects or parts of objects. This step is typically used to identify objects or other relevant information in digital images. There are generic methods available for image segmentation and edge based segmentation is one among them. Image segmentation needs to segment the object from the background to read the image properly and identify the content of the image carefully. In this context, edge detection is considered to be a fundamental tool for image segmentation. Keywords :- Digital image processing, image segmentation, edge detection. I. INTRODUCTION and digital image processing. Analog Image Processing refers to the processing of image The term image processing refers to through electrical means. The most common processing of images using mathematical operations example is the television image. The television in order to get an enhanced image or to extract some signal is a voltage level which varies in amplitude useful information from it. It is a type of signal to represent brightness through the image. By dispensation in which input may be image like electrically varying the signal, the displayed image video frame or photograph and output may be image appearance is altered. The brightness and contrast or characteristics associated with that image. Image controls on a TV set serve to adjust the amplitude processing is a rapidly growing technology today, and reference of the video signal, resulting in the with its diverse applications in various aspects of brightening, darkening and alteration of the science, engineering, management, business and day brightness range of the displayed image. In Digital to day life activities and it is a core research area Image Processing, digital computers are used to too. Image Processing is a technique useful in process the image. The image will be converted enhancing raw images received from cameras or into digital form using a scanner or digital sensors placed for various applications including camera and then fed as input for processing enhancing images obtained from unmanned operations by digital computer. Digital image spacecrafts, space probes and military processing includes numerous procedures such as reconnaissance flights[1]. Image processing finds formatting and correcting of the data, digital applications in areas such as Remote Sensing, enhancement to facilitate better visual interpretation, Medical Imaging, Non-destructive Evaluation, or even automated classification of targets and Forensic Studies, Textiles, Material Science, features entirely by computer. The requirements for Military, Film industry, Document processing, digital image processing is a computer system, Graphic arts and Printing Industry. sometimes referred to as an image analysis system, The following sections describe different steps in with the necessary hardware and software to process image processing, specifically edge based image the data. There are efficient software systems, open segmentation and image edge detection techniques in source and proprietory, have been developed for detail. image processing. The term digital image processing generally refers to processing of a two-dimensional picture by a digital computer and II.METHODS OF IMAGE a digital image is an array of real numbers PROCESSING represented by a finite number of bits[2]. The main There are two types of methods used in Image advantage of Digital Image Processing methods is Processing and they are Analog image processing its repeatability, versatility and the preservation of ISSN: 2347-8578 www.ijcstjournal.org Page 126 International Journal of Computer Science Trends and Technology (IJCST) – Volume 2 Issue 4, Nov-Dec 2014 original data accuracy. units that are either more meaningful or more efficient for further analysis. The main reasons for the growing interest and Segmentation separates an image in to its demand in digital image processing are due to its component regions or objects. Image segmentation applications such as (i) improvement of pictorial needs to segment the object from the background to information for human interpretation, and (ii) read the image properly and to identify the content processing of scene data for autonomous of the image carefully. Because of the same reason, machine perception. edge detection is a fundamental tool for image segmentation. Example for the first application area are the iv)Representation and description: Representation is enhancement of images in medical field such as transforming raw data into a form suitable for MRI image, X-ray image etc to improve the computer processing. Description, which is also pictorial content of it, thus making it easier for called feature extraction, deals with extracting human interpretation. The second application area features that result in some quantitative information focuses on procedures for extracting image of interest or features which are basic for information in a form suitable for computer differentiating one class of objects from another. processing. Examples include automatic character v)Recognition & Interpretation : Recognition is the recognition, industrial machine vision for product process which assigns a label to an object based on assembly and inspection, military the information provided by its descriptors. recognizance, automatic processing of Interpretation is the process of assigning meaning to fingerprints etc. an ensemble of recognized objects. Of the different steps mentioned above, image III.STEPS IN IMAGE PROCESSING segmentation, which has emerged as a significant phase in image based applications, is going to be There are some common steps in image processing dealt in detail in the following section. as listed below, though all image processing systems would not require all steps together. IV. IMAGE SEGMENTATION i)Image Acquisition : An image is captured by a Image segmentation, one of the significant aspects sensor such as a TV camera and then it is digitized. of image processing, is a long standing problem in ii)Image Preprocessing : The first step in preparing the research area of computer vision. The main aim the picture for higher-level processing is called pre- of segmentation is to extract the ROI(Region of processing and the purpose of pre-processing is two- Interest)for image analysis. The division of an image fold: to eliminate undesirable features that will into meaningful structures, ie., image segmentation, hinder further processing and to extract the is often an essential step in image analysis, object desirable features that represent useful information representation, visualization, and many other image in the image. Unwanted image attributes include processing tasks. Segmentation plays an important noise (insignificant lines and contours) and the role in image processing since separation of a large presence of featureless space and the important image into several parts makes further processing features include surface details and boundaries such simpler. These several parts that are rejoined will as lines, edges, and vertices. Image preprocessing cover the entire image. Segmentation may also typically includes a processing step of transforming depend on various features like colour or texture a source image into a new image which is that are contained in the image. Before denoising fundamentally similar to the source image, but an image, it is segmented to recover the differs in certain aspects, e.g. improved contrast. In original image. The main aim of segmentation is this step, computer suppresses noise and sometimes to reduce the information and hence making easy enhances some object features which are essential in analysis possible. understanding the image. iii)Image segmentation: The main aim of There exists several image segmentation techniques, segmentation is to reduce the information to enable which partition the image into several parts based on easy analysis. Segmentation is also useful in Image certain image features like pixel intensity value, Analysis and Image Compression[3]. In this color, texture, etc and these techniques are process, an image is divided into multiple parts and categorized based on the segmentation method used. this is typically used to identify objects or other A great variety of segmentation methods has been relevant information in digital images. The proposed till now and in this article, we will segmentation has two objectives - i. to decompose concentrate on edge based segmentation methods the image into parts for further analysis. ii. to and edge detection mechanisms. In edge based perform a change of representation. ie., The pixels segmentation technique, detected edges in an image of the image must be organized into higher-level are assumed to represent object boundaries, and are ISSN: 2347-8578 www.ijcstjournal.org Page 127 International Journal of Computer Science Trends and Technology (IJCST)