Texture is an important characteristic for the analysis of many types of images because it provides a rich source of information about the image. Also it provides a key to understand basic mechanisms that underlie human visual perception. In this paper four statistical feature of texture (Contrast, Correlation, Homogeneity and Energy) was calculated from gray level Co-occurrence matrix (GLCM) of equal blocks (30×30) from both tumor tissue and normal tissue of three samples of CT-scan image of patients with lung cancer. It was found that the contrast feature is the best to differentiate between textures, while the correlation is not suitable for comparison, the energy and homogeneity features for tumor tissue always greater than its values for normal tissue.
This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4
... Show MoreThis paper aims to early study of detection and diagnosis of kidney tumors and kidney stones using Computed Tomography Scanning CT scan images by digital image processing. Computerized Axial Tomography (CAT) is a special medical imaging technique that provides images with 3D, including much information about the body's construction consisting of bones and organs. A C.T scan uses X-rays to create cross-sectional images of the body and gives the doctor a full explanation of the diagnosis of the situation through the examination. It has been used in five cases of kidney images, including healthy, stones, tumors (cancer), cystic and renal fibrosis. The masking procedure is used to separate the required C.T. images
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Digital images are open to several manipulations and dropped cost of compact cameras and mobile phones due to the robust image editing tools. Image credibility is therefore become doubtful, particularly where photos have power, for instance, news reports and insurance claims in a criminal court. Images forensic methods therefore measure the integrity of image by apply different highly technical methods established in literatures. The present work deals with copy move forgery images of Media Integration and Communication Center Forgery (MICC-F2000) dataset for detecting and revealing the areas that have been tampered portion in the image, the image is sectioned into non overlapping blocks using Simple
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Measuring goat weight on a farm is carried out by two methods. The first method conventionally measures the chest girth (CG) and body length (BL), while the second is performed using a scale. This study aimed to facilitate the CG and BL measurements to estimate goat weight more efficiently through image processing. The endpoints of CG and BL were determined automatically using binary large object (BLOB) segmentation. The images of 120 goats were taken at three different shooting distances of 50 cm, 70 cm, and 90 cm. The statistical testing of the three scenarios in this study explained that the ideal distance to take pictures is the basis for determining whether or not the size of the circumference and BL is appropriate as a fea
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Non Uniform Illumination biological image often leads to diminish structures and inhomogeneous intensities of the image. Algorithm has been proposed using Morphological Operations different types of structuring elements including (dick, line, square and ball) with the same parameters of (15).To correct the non-uniform illumination and enhancement biological images, the non-uniform background illumination have been removed from image, using (contrast adjustment, histogram equalization and adaptive histogram equalization). The used basic approach to extract the statistical features values from gray level of co-occurrence matrices (GLCM) can show the typical values for features content of biological images that can be in form of shape or sp
... Show MoreEchocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.
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This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods