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In this work, we proposed a novel authentication system based on facial features. The proposed method is based on PCA and LDA for feature extraction, these extracted features are combined using wavelet fusion. In this work we use neural networks to classify extracted features of faces. The proposed method consists of six steps: i) Extraction of images from the database, ii) Preprocessing, iii) Feature...
In this paper we are using Devanagari script OCR for recognition. The handwritten data set is created by us and for printed characters we have used ISM font. Here we are using gradient and curvature based feature extraction method. We have compared Nearest Neighbor, K-Nearest Neighbor, Euclidian Distance-based K-NN, Cosine Similarity -based K-NN, Condensed Nearest Neighbor, Reduced Nearest neighbor,...
Illumination and expression variation are the major challenges in the face recognition. This paper presents comparative analysis of two normalization techniques namely, DCT in Log domain and 2-point normalization method.. The DCT is employed to compensate for illumination variations in the logarithm domain. Since illumination variation lies mainly in the low frequency band, an appropriate number of...
In content-based image retrieval, it is helpful to add a pre-classification module to classify a query image into attentive class or non-attentive class. Based on the pre-classification result, a suitable retrieval strategy is adopted for the query image presented. In this paper, we proposed a Multi-Layer Perceptron (MLP) classifier with the features extracted from saliency map to classify both the...
Medical Diagnosis is the utmost need of an hour. Gestational Diabetics in women represents the second leading cause of yielding children born with birth defects. The ultrasound images are usually low in resolution making diagnosis difficult. Specialized tools are required to assist the medical experts to categorize and diagnose diseases to accuracy. If the anomalies in the ultrasound images are detected...
India is a multi-lingual multi-script country, where eighteen official scripts are accepted and there are over hundred regional languages. In this paper we propose a zone-based hybrid feature extraction algorithm scheme towards the recognition of off-line handwritten numerals of two popular south-Indian scripts. The character centroid is computed and the character/numeral image (50 ?? 50) is further...
Artificial neural networks are significantly used in the field of ophthalmology for accurate disease identification which further aids in treatment planning. In this paper, an automated system based on Self-Organizing neural network (Kohonen network) is proposed for eye disease classification. Abnormal retinal images from four different classes namely non-proliferative diabetic retinopathy (NPDR),...
We propose a new ultrasonic image analysis system that can be utilized as an effective tool in classifying liver states as normal, hepatitis, or liver cirrhosis. In this system, we first define suitable settings for the ultrasonic device, then remove the inhomogeneous structures from the area of interest in the image, and then, by using the forward sequential search method, look for the useful texture...
In this work, a new system for Arabic letter recognition is designed and implemented. New approaches for segmentation, processing, classification and hence recognition of characters and scripts are shown. The research concentrates on two important subjects: First, segmentation on the basis of word histogram and baseline estimation - a convenient algorithm is worked out for this aim. Second, the process...
Autofluorescence bronchoscopy (AFB) has been utilized over the past decade, proving to be a powerful tool for the detection and localization of premalignant and malignant lesions of the airways. AFB is, however, characterized by low specificity and a high rate of false positive findings (FPFs). The majority of FPFs are due to inflammations, as they often fluoresce at the same wavelengths with cancer...
Image classification plays an important role in many tasks, which is still a challenging problem. This paper proposes a hybrid image classification method, which integrates wavelet transform, rough set approach, and artificial neural networks (ANNs). Wavelet transform is employed to decompose the original images into different frequency sub-bands, then a set of statistical features are extracted from...
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