International Journal of Computer Applications (0975 – 8887) Volume 61– No.9, January 2013 28 Implementing Edge Detection for Detecting Neurons from Brain to Identify Emotions Madhulika Assistant Professor, Department of Computer Science Engineering Amity University Noida, India Abhay Bansal, PhD. Professor, Head Department of Computer Science Engineering Amity University Noida,India Amandeep Assistant Professor, Department of Computer Science Engineering Amity University Noida, India Madhurima Assistant Professor, Department of Computer Science Engineering Amity University Noida, India ABSTRACT Edges of an image are considered a type of crucial information that can be extracted by applying detectors with different methodology. Edge detection is a basic and important subject in computer vision and image processing In this Paper we discuss several Digital Image Processing Techniques applied in edge feature extraction. Firstly, Linear filtering of Image is done is used to remove noises from the image collected. Secondly, some edge detection operators such as Sobel, Log edge detection, canny edge detection are analyzed and then according to the simulation results, the advantages and disadvantages of these edge detection operators are compared. It is shown that the canny operator can obtain better edge feature. Finally, Edge detection is applied to identify neurons in Brain. After this the Neurons are classified and feature vector will be calculated. Keywords- Filters, Sobel, Canny, Log, Distortion, Edge Detection Introduction (Heading 1) 1 INTRODUCTION Detecting edges is types of Image Segmentation Techniques which shows the presence of edges or line in an image and give them boundaries in an appropriate way [1].The edge is a set of those pixels that exists between object and background, object and object, region and region, and between element and element. Edge always exists with different grey level in two neighboring areas .Edge detection based on range non- continuity. Image edge detection is one of the important contents in the image processing and analysis, and also is a kind of issues which are unable to be resolved completely so far [2]. When image is acquired, there are so many factors like projection, mix, aberrance and noise are produced. These factors effect on image feature’s making it blur and distortion, consequently it is very difficult to extract image feature. Moreover, due to such factors it is also difficult to detect edge. The method of image edge detection and extraction is very hot research topic in the domain of image processing and analysis technique. Edge feature extraction has been applied in many areas widely. This paper mainly discusses about several edge detection operators and applied in the detecting Neurons in it .Firstly the acquired image is filtered and denoised. In the process of denoising, Linear Filter is used. And then different operators are applied to detect edge including Sobel operator, Log operator, Canny operator. Finally the edge detection is applied to detect neurons in human brain. . 2 LOAD IMAGE IN MATLAB A Loading Original image in Matlab The image is loaded in Matlab by GUI developed using GUIDE tool. The original image of a Neuron is loaded using a load module. Figure 1 Original image of a Neuron in Human Brain 3 IMAGE FILTERING  Linear filter The Image is filtered using Low pass and high pass filter. Low pass filtering, It is also called "smoothing". It helps us to employ or to remove high spatial frequency noise from a digital image. Noise is often introduced during the analog-to- digital conversion process as a side-effect of the physical conversion of patterns of light energy into electrical patterns [3]. Smoothing is done in Low Pass Filtering. In Edges are detected using High Pass Filtering. The original image is loaded then filtered using imfilter function in Matlab.