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In this paper, we develop an methodology and corresponding algorithms that segments regions of interest like vegetation and flood from aerial images. To this end different textural features are used, particularly second order type (extracted from co-occurrence matrix — Haralick features) and histogram of oriented gradients (HOG). These features are calculated from image patches and the obtained values...
Because there are many false targets in the seabed imaging of SAS (synthetic aperture sonar), it is difficult for the automatic alarm of buried column targets. An automatic alarm method for buried targets based on membership classification is proposed in this paper. Firstly, the mean-standard deviation maximum entropy segmentation is used to segment seabed image. Then the area and posture ratio of...
Natural disasters such as earthquakes and tsunamis often have a devastating effect on human life and cause noticeable damage to infrastructure. Active research has been ongoing to mitigate the impact of these catastrophes and preclude the economic losses. The existing methods that utilize pre-event and post-event images not only require the immediate and guaranteed availability of the appropriate...
Automatic airport detection has received great attention due to the importance of airports in both military and civilian uses. This paper focuses on automatic airport detection in large-size remote sensing images under a two-step object detection framework. In the first step, both geometrical saliency and local entropy saliency are improved to find more accurate ROIs for detecting airports in large-size...
This article presents to detect lung tumor, classification and area recognition system. Nowadays, Lung tumor is major cause of death for all the people. Early detection of lung tumor plays an important part to enhance chance for survive to live. Early detecting of tumor is a important role for the treatment where Computed Tomography (CT) screening are consider as appropriate method for detecting the...
Image segmentation is a basic task in image analysis and understanding and feature extraction is important but difficult. In this paper, we propose an effective feature selection method for color image segmentation which selects a group of mixed color features or channels from some different color spaces according to the principle of the least entropy of pixels frequency histogram distribution. Actually,...
In the paper, we present a method for evaluating the quality of tongue images in Traditional Chinese Medicine (TCM). First, we preprocess the original images to segment the tongue images. Second, geometric features, texture features and spectral entropy features and spatial entropy features based on Spatial-Spectral Entropy-based Quality (SSEQ) index of tongue images are extracted respectively to...
The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques...
The function of visual attention mechanism is to acquire the useful visual information at the fastest speed. The Itti visual attention model commonly used at present has achieved good effects in natural image. In order to find the region of interest as soon as possible, this paper attempts to introduce visual attention mechanism into pulmonary nodules detection. However, the Itti model is more to...
Acoustic Radiation Force Impulse (ARFI) imaging is a type of ultrasound elastography used in medicine, particularly for the monitoring and diagnosis of cancers. Medical professionals observe the tissue elasticity of the ARFI equipment for the diagnosis of the cancer. This paper investigates the role of image processing on the ARFI image for the diagnosis of breast tumour. Initially, in the pre-processing...
In the web pages contains large and vast amount of data, which is rich source of information available to everyone in the world through Internet. However the web page is combination of noisy data like navigational link, advertisements, menus, footer, etc and informative data, so the complexity may increases for main content extraction from web pages. To access main content hand crafted rule technique...
Segmentation process of an Image, represents meaningful way for further analysis and use in medical imaging, remote sensing and military objects detection. Due to poor resolution, segmentation become complex especially is an image is blurred or mixed pixels. Active contour technique is popular to get smooth curve around the boundary of 2D images but due to image gradient this techniques is unable...
This paper discusses about a method adopted to develop a computer-aided diagnostic system to achieve automatic detection and classification of liver lesions. The procedure followed consists of first segmenting the CT scan image so as to accurately extract out the lesion region alone from the rest of the abdominal details. This Region Of Interest(ROI) is now used up for extracting out first order and...
Feature Selection in medical image processing is a process of selection of relevant features, which are useful in model construction, as it will lead to reduced training times and classification model designed will be easier to interrupt. In this paper a meta-heuristic algorithm Artificial Bee Colony (ABC) has been used for feature selection in Computed Tomography (CT Scan) images of cervical cancer...
Due to their role in certain essential forest processes, dead trees are an interesting object of study within the environmental and forest sciences. This paper describes an active learning-based approach to detecting individual standing dead trees, known as snags, from ALS point clouds and aerial color infrared imagery. We first segment individual trees within the 3D point cloud and subsequently find...
One open problem in the fields of place recognition and mapping is to be able to recognise a revisited place when its appearance and layout have changed between visits. In this paper, we investigate this problem in the context of RGB-D mapping in indoor environments. We propose to segment the scene in juts (neighbourhood of 3D points with normals that stick out from the surroundings) and look at low-level...
Even though a number of anatomical structures contribute to the process of vision, many eye disease that causes blindness occur mainly in the retina. One among the important eye disease is Diabetic Retinopathy. DR is a severe eye disease and is the primary cause of blindness in the case of diabetic patients. We describe a novel method for automatically detecting the exudates with the help of retinal...
In this study, a method of thresholding is proposed that based on the histogram shape of each image, proposes the more appropriate technique from the famous and common thresholding techniques. Thresholding, which is a commonly used operation for image processing, is the selection of one of the image pixels that determines the border for background and foreground of the image. After determining a suitable...
In this paper, a computer vision based system is introduced to automatically grade apple fruits. Segmentation of defected skin is done by three global thresholding techniques (Otsu, isodata and entropy). Stem-end/calyx regions falsely classified as defect are removed. Segmentations were visually best with isodata technique applied on 750nm filter image. Statistical features are extracted from the...
This study aims to provide detailed spatial information of valuable tree species to support improved management of winter habitat of white-tailed deer. To achieve this, we proposed a novel approach using information from two spatial scales and a suite of methods for analysis and classification of remotely sensed data. High-spatial resolution, multispectral images were employed to test the proposed...
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