1.4% Reino Unido
3. LA PRODUCCIÓN ESPACIAL Y LAS FORMAS DE DESPOJO DEL PROYECTO MINERO “CERRO JUMIL”.
Image of carotid artery that obtains will be converted into the grayscale to fix the size and shape of the image. This process is to facilitate the interpretation of ultrasound image through the image reduction and edge enhancement. The grayscale image then undergoes the filtering techniques in image segmentation. In this project, three types of filtering which are Gaussian blur (Gaussian filter), Median filter and Histogram Equalization filter are used. When the SNR value is high and the noise is low, the image has high resolution and the clearer image is produced. Edge detection is one of technique that used in the image processing to extract useful information. In medical research, edge detection is an important method that applied for object recognition of the human organs such as lungs and ribs, and it is an essential pre-processing step in medical image segmentation [22] [23]. By using MATLAB software, there has a several types of edge detection with a specific command that represent the different function and advantages such as Robert operator, Sobel operator, Prewitt operator, and Canny operator. In this study, the proposed edge detection operator is a canny operator. There have several types of edge detection that used in image and video processing. In industries, the standard edge detection method that is usually considered to use is a canny operator [24]. Canny operator is more approximate and way, compared to the previous method, which has a complex exponential solution. Besides, the canny edge detection used to detect the wide range of edges in images and also video.
24
Image of carotid artery after image processing
The original image was cropped according to the specified coordinates which are at [91.5 127.5 453 117] as shown in Figure 3.8.
(a)
Figure 3.8 : (a) Image of carotid artery, (b) Carotid Artery image in the specific coordinate.
Every subject has different specific coordinates that cropped because of different size and diameter of carotid artery. After that, image crop will convert into grayscale to fix size and shape of image. This process is to facilitate the interpretation of ultrasound image through the image reduction and edge enhancement.
The grayscale image then undergoes the filtering to removes noise. It is because most of the imaging ultrasound are contaminated with noise. Therefore, filtering is introduced to reduce the noise in order to clearly visualise the shape of the carotid artery. In this project, Wiener filter is applied because of Wiener is one of the most fundamental noise reduction methods. In addition, this filter has been implemented widely in the noise reduction in ultrasound image. Other than that, Wiener filter also performs smoothing of the image based on the computation of local image variance. When the local variance of the image is large the smoothing is little on the other hand if the variance is small, smoothing will be better [27]. Besides, Wiener filter can be used as decorrelator of speckle, which makes its distribution more in reflectivity. If reflectivity is reasonably assumed to be corrupted by multiplicative noise then eliminate such noise [28].
Next, the image will undergo the local adaptive thresholding. There are two types of thresholding based method namely local and global. In this process, local adaptive is applied as it can overcome the limitation of conventional threshold method when the image background or the feature intensities are not homogeneous. In contrast, global
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