A Study of Frei-Chen Approach for Edge Detection

Digital image processing is a computational process that is widely used today starting from editing photos or also the manipulation of the picture, one form of image processing is edge detection, edge detection in images is one technique that can be used to mark parts into detail of the picture, either a blurred image due to error or the effect of the image acquisition process, in this study using the Frei-Chen algorithm to perform edge detection image in order to know the borders of the picture


I. INTRODUCTION
Digital image is a picture of an object that is an analog form of video signals, or digital can also directly stored on a storage media such as flash and various other storage media [1] [2]. The use of digital images has increased because of the advantages possessed by the digital image, among other things ease in obtaining imagery, image processing, and others. But not all digital images have a pleasing visual appearance of the human eye [1] [2].
One form of image processing that can use is the edge detection [1] [3]. Edge detection is common in digital image processing because the first step in image segmentation, image segmentation is used to present the objects contained in a picture [3] [4] [5]. Edge detection function to identify the boundaries of an object on the image overlap [6]. Therefore, when the outline of the picture can identify accurately, all objects can be found, and basic properties such as area, shape, and size of the object can be measured [6] [7]. The edges of the image are the position where the intensity of the pixels of the picture changed from low value to high value or vice versa [7]. Currently, there are several methods that can use for edge detection, for example, is a method Sobel, Canny, Prewitt, Frei-Chen and Laplacian [4] [8] [9] [10]. This study uses Frei-Chen, Frei-Chen an edge detection method using the Frei-Chen mask which contains the base vector calculation to be applied to the image [11]. Frei-Chen pointed a simple edge detector best does edge detection, followed by thinning and linking processes to optimize the margins [1] [8]. This research tries to apply the method Frei-Chen to perform edge detection in digital images with the help of tool Matlab.

II. METHODS AND MATERIAL
The image is the visual representation of an object [1] [2], the output of a system such as optical data recording in the form of photos or also the analog video signal form as the image on the monitor and also directly stored on a storage medium [2]. Images grouped into two parts, namely the still image and a moving image. The still image is a single image that is not moving. Instead, the moving image is a series of a still image is displayed in a sequence, thus giving the impression to the eye as a moving picture [2].

Edge Detection
Edge detection is the first step to cover the information in the image, the edges characterize the boundaries of the object, therefore, useful to the process edge segmentation and identification of objects in the picture. Interest edge detection operation is to improve the appearance of the boundary line of an area or object in the image [4] [5] [6] [9] [11].

Convolution
Implementation of a filter on an image used a technique called convolution [2], convolution is express in the form of a matrix n, where each element is called coefficient convolution matrix [1] [9] [10]. Process convolution kernel works by shifting pixels per pixel, which results stored in the new matrix. Here is an example of the convolution that occurs between image f (x, y) 5x5 with a 3x3 kernel shown in the following figure.

Frei-Chen Algorithm
Edge detection using Chen Frei implemented by mapping a vector mask intensity using linear transformations, and then detect the intensity of the edge based on the angle between the vectors are projected into space the edges.

III. RESULTS AND DISCUSSION
The process of testing Frei-Chen algorithm in edge detection performed in the following figure ( ) The next is to determine the kernel that is used to detect the image, this kernel function to be used as a base count by using algorithms Frei-Chen here is the kernel

[ √ √ ]
After determining the value of the next kernel image and calculate the value of the convolution of the picture.   The next process is the kernel shift one pixel to the right, then calculate the pixel value at the position (0,0) of the kernel     above values a the final value calculation process by using algorithms Frei-Chen, from the calculation, the result of edge detection of Figure 1 is as follows:

IV. CONCLUSION
Frei-Chen algorithm testing at the image edge detection can be done well with good results, from the count of kernel algorithms Frei-Chen conducted the process is also easy to do, and the application is made using a tool like Matlab image processing is relatively easy.