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The most important factor in reduction of quality and quantity of crop is due to plant disease. Identifying plant disease is a key to prevent agricultural losses. The aim of this paper is to develop a software solution which automatically detect and classify plant disease. It includes four steps, first step image acquisition, second step is image preprocessing, third step is image segmentation and...
Paddy is the most important crop in Asian country. Most of the people depend on rice for their food, so rice is considered as staple food in Asian country. Rice plant is affected by many diseases that affect the farmers in yield loss. In this paper, proposed a method for identification of Blast and Brown Spot diseases. Global threshold method has been applied and kNN classifier has been used to classify...
In the world today there are number of skin diseases which are found in humans, animals and plants. The illness caused by bacteria or infections will be known as skin disease like yeast infection, allergy, eczema, brown spot. These skin diseases have dangerous effect on skin and they keep on spreading over time. To control them from spreading it is necessary to identify these diseases at their starting...
Agriculture is the foundation of our country. India is an agrarian nation where the majority of the populaces rely upon agribusiness. Investigation in farming is pointed towards expanding efficiency and profit. There are several automated systems already available which are developed for irrigation control and environmental monitoring in the field. Hence this project aims to monitor the plant growth...
Agrarian production is that trait on which our nation's economy immensely depends. This is the motivation that recognition of leaves unhealthiness is the solution for saving the reduction of crops and productivity. It requisite enormous amount of work, mastery in the leaf diseases, and additionally need the extreme amount of time. Thus, image processing techniques are applied for the discovering and...
Plants are one of the major resources to avoid the global warming in the world. But the plants are affected by the diseases like Blast, Canker, Black spot, Brown spot, Bacterial leaf Blight and Cotton mold. The objective of this paper is to recognize the paddy diseases. Some of the paddy disease is Blast Disease (BD), Brown spot Disease (BPD), Narrow Brown spot disease (NBSD), which stops the growth...
Reliable automatic system for Human Epithelial-2 (HEp-2) cell image classification can facilitate the diagnosis of systemic autoimmune diseases. In this paper, an automatic pattern recognition system using fully convolutional network (FCN) was proposed to address the HEp-2 specimen classification problem. The FCN in the proposed framework was adapted from VGG-16, which was trained with ICPR 2016 dataset...
Retinal image analysis is increasing popularity for the detection of eye disease like diabetic retinopathy, glaucoma, cardiovascular disease. In modern ophthalmology, the structure of retinal image with proper segmentation has achieved much interest for disease detection. This paper presents a method with some new features extraction methodology after applying segmentation procedure in retinal images...
Confocal Laser Endomicroscopy (CLE) is a technique permitting on-site microscopy of the gastrointestinal mucosa after the application of a fluorescent agent, allowing the evaluation of mucosa alterations. These are used as features by skilled technicians to stage the severity of multiple diseases, celiac disease or irritable bowel syndrome among the others. We present an automatic method for villi...
Identification of the plant diseases is the key to preventing the losses in the yield and quantity of the agricultural product. The studies of the plant diseases mean the studies of visually observable patterns seen on the plant. Health monitoring and disease detection on plant is very critical for sustainable agriculture. It is very difficult to monitor the plant diseases manually. It requires tremendous...
Malaria is a serious worldwide health issue which causes globally an expected 3.4 billion individuals in danger of malaria in 2013. Malaria is an entirely preventable and treatable disease [1]. For fast diagnosis and acute treatment of Malaria is important to reduce the death rate. As the parasite changes morphology in its different life stages and its types varies, an experienced technician is required...
The extraction of nucleus from the blood smear images of white blood cells (WBC) provides the valuable information to doctors for identification of different kinds of diseases as most of the diseases present in body can be identified by analyzing blood. Manually it very soporific and tiresome to segment the nucleus and after that classification is done on the basis of that besides that the instruments...
Plant disease management is an important factor in agriculture as it causes a significant yield loss in crops. Late Blight is the most devastating disease for Potato in most of the potato growing regions in the world. For optimum use of pesticide and to minimize the yield loss, the identification of disease severity is essential. The key contribution here is an algorithm to determine the severity...
In current scenario Breast cancer is the most common cause of cancer death in women. Recently, mammography is used as the most convenient examination technique for the detection of early signs of breast cancer. Clustered Microcalcification (MC) in mammograms plays a vital role in indication for early detection of breast cancer. The conventional 2D mammography has a severe limitation of decrease in...
Lung segmentation is an important first step for quantitative lung CT image analysis and computer aided diagnosis. However, accurate and automated lung CT image segmentation may be made difficult by the presence of the abnormalities. Since many lung diseases change tissue density, resulting in intensity changes in the CT image data, intensity-only segmentation algorithms will not work for most pathological...
We propose and evaluate a framework for detection of plant leaf/stem diseases. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively expensive, especially in developing countries. Providing fast, automatic, cheap and accurate image-processing-based solutions for that task can be of great realistic significance. The proposed framework is image-processing-based...
To effectively diagnose and monitor the treatment of diseases such as osteoarthritis, the segmentation, processing and analysis of mass volumes of medical images is gaining high importance. In this paper, a new fully automated content-based segmentation framework is proposed. The framework is designed to be compatible with a wide variety of segmentation techniques. To this end, a novel content-based...
Dyslexia severely impairs learning abilities of children, so that improved diagnostic methods are needed. Neuropathological studies have revealed an abnormal anatomy of the Corpus Callosum (CC) in dyslexic brains. We propose a new approach to quantitative analysis of three-dimensional (3D) magnetic resonance images (MRI) of the brain that ensures a more accurate quantification of anatomical differences...
We consider the problem of detecting the presence of pneumoconiosis in a patient on the basis of evidence found in chest radiographs. Abnormalities pertaining to pneumoconiosis appear in the form of opacities of various sizes; the profusion of these opacities determines the stage of the disease. We present a multiresolution approach whereby we segment regions of interest (ROIs) from the X-Ray image...
Doppler imaging allows evaluation of blood flow patterns, direction, and velocity. The color (red, blue, and mosaic) signify the direction of the blood flow. By analyzing this color Doppler, it is possible to detect heart diseases like mitral and aortic stenosis, mitral, tricuspid, and aortic regurgitation, and Left Ventricle (LV) hypertrophy. We present 3 methods to extract low level features namely...
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