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Extracting and recognizing mathematical expressions of scientific documents are key steps in the process of mathematical retrieval system, where the documents contain different components such as text, tables, figures, and mathematical expressions. There are several methods proposed to handle the components of documents. Those methods have investigated the feature of components based on the segmented...
The frequent occurrence of road congestion and traffic accidents has affected people's travel efficiency and travel safety. Traffic sign recognition has become one of the key research objects in intelligent transportation system. This paper studies the identification of road traffic signs based on video images. First of all, collected image will be image preprocessing with image reduction, brightness...
Digital image processing techniques are commonly employed for food classification in an industrial environment. In this paper, we propose the use of supervised learning methods, namely multi-class support vector machines and artificial neural networks to perform classification of different type of almonds. In the process of defining the feature vectors, the proposed method has relied on the principal...
Melanoma skin cancer is on the rise globally due to increased ultraviolet radiation and even in darker skinned communities, new cases are being discovered. Like many cancers if detected early the chances of successful treatment and cure are high but if detected at a later stage the chances become low. In the application of Computer Aided Diagnosis systems for detection of melanoma, image pre-processing,...
Glaucoma is a group of eye disorders that damage the optic nerve. Considering a single eye condition for the diagnosis of glaucoma has failed to detect all glaucoma cases accurately. A reliable computer-aided diagnosis system is proposed based on a novel combination of hybrid structural and textural features. The system improves the decision-making process after analysing a variety of glaucoma conditions...
The overall aim of the proposed skin lesions classification method is to improve the quality and accuracy of existing skin diagnostic system by establishing superior feature extraction and classification of skin lesions from standard digital images. At first, images of skin lesions are pre-processed by resizing, removing hair, removing noise by filtering and enhancing contrast. Rather than using RGB/HSV/YCbCr...
Ultrasound image is one of the modalities that is widely used to examine the abnormality of thyroid gland since it is relatively low-cost and safety. Fine needle aspiration biopsy (FNAB) is usually used by radiologists to determine the thyroid nodule whether malignant or benign. Commonly, malignancy of thyroid nodule determined based on shape feature. This research proposes a scheme for classifying...
Patten recognition techniques are widely used for image processing in medical imaging. It provides assistance to physicians and scientists in large scale diagnosis. In this paper, we have proposed an automated system for detecting melanoma from dermoscopic images. We detected melanoma by extracting information from region of interest (ROI) rather than the whole image composed of lesion and background...
Diabetic Retinopathy and Diabetic Macular Edema are diseases that affect vision and eventually may lead to blindness. Early detection is a must to prevent the progression of the disease imploring the need for effective computer-aided diagnostic techniques. In the following research paper, a robust method has been proposed to segment hard exudates from digital, color fundus images using anisotropic...
In this paper we present experiments made on an extension of a well-known simple global color criterion and we present the results obtained in iris recognition on two known iris databases, UBIRIS and UPOL. All tests were done for three different color spaces, RGB, HSV and LAB, and two discriminative classifiers, k-NN (k - Nearest Neighborhood) and SVM (Support Vector Machine) were used in our experiments...
Skin cancer is one of the most deadly cancers in the world. If not diagnosed in early stages it might be hard to cure. This paper suggests a new approach for automatic segmentation and classification of skin lesion for dermoscopic images. The segmentation is based on a pre-processing; using the color structure-texture image decomposition to decompose a textured image into texture and geometrical components...
Text recognition has revolutionized the world of image processing and intelligent transportation system (ITS). It opened several possibilities to traditional ITS concept. Advancement in text recognition has made it possible to implement text recognition in ITS. Traffic panel text recognition, a real time application is considered as a key addition to the revolution in modern ITS. This research aims...
Modern phenotyping and plant disease detection provide promising step towards food security and sustainable agriculture. In particular, imaging and computer vision based phenotyping offers the ability to study quantitative plant physiology. On the contrary, manual interpretation requires tremendous amount of work, expertise in plant diseases, and also requires excessive processing time. In this work,...
1p/19q co-deletion is an important prognostic factor in low grade gliomas. However, determination of the 1p/19q status currently requires a biopsy. To overcome this, we investigate a radiogenomic classification using support vector machines to non-invasively predict the 1p/19q status from multimodal MRI data. Different approaches of predicting this status were compared: a direct approach which predicts...
A warning system about drowsy status (fatigue or drowsiness) of the driver, helping to limit the traffic accidents caused by falling asleep behind the wheel by determining the status of the eyes combined with the head direction of driver. In this paper, we present a novel approach for determining the position of a human face and eyes in different directions of the face (turning left, turning right,...
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...
A CAD system for diagnosing the mammograms is proposed in this work. The mammogram image is preprocessed using adaptive median filter and ROI is segmented using otsu's thresholding technique. Then the extracted GLCM features from ROI were given to the classifier. The classifiers such as SVM and KNN were used in this CAD system and the performance metrics were analyzed. The classification accuracy...
Over the years, the growth in medical image processing is increasing in a tremendous manner. The rate of increasing diseases with respect to various types of cancer and other related human problems paves the way for the development in biomedical research. Thus processing and analyzing these medical images is of high importance for clinical diagnosis. This work focuses on performing effective classification...
This paper reports on classification methods applied and tested for land use classification in a semi-arid environment. Our study, conducted on two irrigated sites located in the Kairouan region, the largest irrigated region in Tunisia, compared Support Vector Machine (SVM) and Maximum Likelihood classification of SPOT-7 data. To produce a per-field classification a Mean-Shift Segmentation has been...
A new method of digital number recognition for mechanical digital meters in substation is studied in this paper, which adopts linear SVM based on Histogram of Oriented Gradients (HOG) features. The grids of Histograms of Oriented Gradient descriptors significantly outperform for feature detection of the gray image which has more information than binary image. A new approach with segmentation of region...
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