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Extraction of relevant features from high-dimensional multi-way functional MRI (fMRI) data is essential for the classification of a cognitive task. In general, fMRI records a combination of neural activation signals and several other noisy components. Alternatively, fMRI data is represented as a high dimensional array using a number of voxels, time instants, and snapshots. The organisation of fMRI...
Leaf can be one of the many different parameters on the basis of which a plant can be uniquely identified. Many plants types are on the verge of extinction and can be taken care of, if identified correctly. The proposed method discusses an automated image processing system for leaf classification. The leaf pixels from the image are segmented and termed as region of interest (ROI). A set of geometrical,...
Sign Language, which is a fully visual language with its own grammar, differs largely from that of spoken languages [21]. After nearly 30 years of research, SL recognition still in its infancy when compared to Automatic Speech Recognition. When producing Sign language (SL), different body parts are involved. Most importantly the hands, but also facial expressions and body movements/postures. The recognition...
Uveal melanoma is a type of tumor that can cause loss of vision, loss of organ or even metastasis and loss of life. Radiotherapy is considered to be the least harmful and successful treatment type among various treatment methods. Radiotherapy should be carried out sensitively without movements of the iris. Therefore, the procedure is mostly performed by local anesthesia. Unfortunately, eye anesthesia...
The “Nuclear Seed Recognition and Weed Segregation System (NSRWSS)” aims at simplifying the task of identification and classification of seed varieties using Image Processing techniques. Seed recognition and weed segregation consumes a lot of manual labor in seed production industries. NSRWSS can accomplish weed and damaged seed separation for various crops. Genetic purity, which is given top most...
In this paper, a novel random-valued impulse noise (RVIN) detection based-on neural network is proposed. In order to precise noise detection, the feed-forward neural network with back-propagation training algorithm is applied. Five features of noisy images are extracted and used as input of the proposed network. Thus, the uncorrupted and corrupted pixels can be precisely classified. Experimental results...
One of the dominant causes of visual impairment worldwide is Cataract. It causes a blurred and foggy vision which can lead to partial or complete loss of eyesight. A protein layer is developed gradually and the lens becomes cloudy over a long period of time which reduces vision and leads to blindness. Early treatment can lessen the difficulties faced by cataract patients and avert visual impairment...
Ultrasound (US) Doppler spectrograms have been widely used for diagnosing vascular obstructions. This paper presents an Android smartphone based new approach for detecting the blood flow condition based on the US Doppler spectrogram images. A set of 59 spectrograms acquired from a US Doppler system is processed to extract features, and these non-redundant features are fed into a supervised classifier...
Tiny target detections, especially power line detection, have received great attention due to its critical role in ensuring the flight safety of low-flying unmanned aerial vehicles (UAVs). In this paper, an accurate and robust power line detection method is proposed, wherein background noise is mitigated by an embedded convolution neural network (CNN) classifier before conducting the final power line...
Analysis of lace texture images is a challenging problem because the lace is a soft and extensible material and can be easily deformed. This paper investigates a whole system for lace classification. A first step, based on Otsu's segmentation method, allows to remove the background. Then the lace texture is characterized using local binary patterns (LBP). In order to be robust against rotation the...
Bio-medical imaging is playing an important role in the laboratory research, clinical practice, diagnosis and treatment of various diseases. Papilledema is an optic disc swelling, which is occurred due to increased Intracranial Pressure (ICP) of cerebrospinal fluid. Papilledema is the only initial guess for many underlying diseases, therefore, early detection of edema is very essential in emergency...
We propose a new methodology to detect social aspects of crowds in video sequences based on pedestrian features, which are obtained through image processing/computer vision techniques. The main idea is to apply and extend the concepts of Fundamental Diagram (FD) with more features, such as grouping and collectivity. Using crowd features we identify the crowd type and the main characteristics. In addition,...
There is currently a large amount of histopathological images due to the intensive prevention screening programs worldwide. This fact overloads the pathologists' tasks. Hence, there is a connected high need for a quantitative image-based evaluation of digital pathology slides. The current work extracts 76 numerical features from 357 histopathological images and focuses on the selection of the most...
It is challenging to develop an intelligent agent-based or robotic system to conduct long-term automatic health monitoring and robust efficient disease diagnosis as autonomous e-Carers in real-world applications. In this research, we aim to deal with such challenges by presenting an intelligent decision support system for skin lesion recognition as the initial step, which could be embedded into an...
Disease infection to agricultural products like plants, fruits and vegetables, results in degradation of quality and quantity of agriculture products. This directly affects the financial source of agriculturists and the human health. Hence, detection of diseases in plants, fruits and vegetables crops at early stages of development leads to reduce loss of yield and quality. The traditional approaches...
This work presents a method for identifying plant leaf disease and an approach for careful detection of diseases. The goal of proposed work is to diagnose the disease of brinjal leaf using image processing and artificial neural techniques. The diseases on the brinjal are critical issue which makes the sharp decrease in the production of brinjal. The study of interest is the leaf rather than whole...
Identifying disease from the images of the plant is one of the interesting research areas in computer and agriculture field. This paper presents a survey of different image processing and machine-learning techniques used in the identification of rice plant diseases based on images of disease infected rice plants. This paper presents not only survey of various techniques but also concisely discusses...
Malaria is a deathly disease caused by parasites that are transmitted to human through the bite of infected Anopheles mosquitoes. One of these parasites, P. Falciparum can progress to severe illness and often lead to death if not treated within 24 hours. Thus, early diagnosis of parasites in the red blood cell is crucial to decrease the number of malaria victim. Manual diagnosing require a well trained...
Since extremely powerful technologies are now available to generate and process digital images, there is a concomitant need for developing techniques to distinguish the original images from the altered ones, the genuine ones from the doctored ones. In this paper we focus on this problem and propose a method based on the neighbor bit planes of the image. The basic idea is that, the correlation between...
Good body posture is important because it helps to reduce the risk of musculoskeletal injuries and permanent distortions which may interfere with efficient functioning of the body. Individuals need to be aware that good body posture is vital for a healthy quality of life, especially as one ages. However, an individual's ability to detect poor posture can be difficult as a faulty posture tends to feel...
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