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In this paper, we present the ATM (Awesome Translation Machine), which translates handwriting texts in English into Chinese, and then provides its pronunciations in both the two languages. Specifically, two types of the databases that contain characters and sentences for training the ATM are constructed. Various signal processing techniques are employed sequentially for processing and analyzing the...
The thyroid gland is highly vascular organ, and lies in the anterior part of the neck just below the thyroid cartilage. Ultrasound imaging is most commonly used to detect and classify abnormalities of the thyroid gland. Other modalities (CT/MRI) are also used. There is a challenge to segment ultrasound medical image which is often blurred and consists of noise as other modalities like CT contains...
Magnetic Resonance Imaging (MRI) results in overall quality that usually calls for human intervention in order to correctly identify details present in the image. More recently, interest has arisen in automated processes that can adequately segment medical image structures into substructures with finer detail than other efforts to-date. Relatively few image processing methods exist that are considered...
Plastics are used in a truly vast number of applications, and research is continously carried out to improve every aspect of the plastics industry. A recent study of laser transmission welding [1] required cross-sectional images of the weld's microstructure to be analyzed for the presence of pores, which are tiny bubbles that may form during the weld process. It is believed that the number and size...
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference. The corruption in the anchor signal involves intensity modulations, linear distortions, structured interference, clutter, and noise just to name a few. The proposed setup reflects nontrivial prediction scenarios involving...
Many existing source camera classification methods involve either training a classifier or computing the reference pattern noise of a camera, which means a set of images of known origins have to be pre-acquired. However, such requirement can not always be satisfied in real-world forensic applications. In this work, we propose a graph based approach that requires no extra auxiliary images nor a prior...
Visual textual CAPTCHAs have been widely used on Internet banking in China to defend against malicious bot programs. In this paper, four categories of representative CAPTCHAs are chosen to break. We present an efficient method for solving visual textual CAPTCHAs using image processing techniques and instance learning, such as graying, thresholding, interference noises removing, segmentation, character...
Detecting the region of a license plate is the key component of the vehicle license plate recognition system. The spatial frequency characteristic in the license plate region usually varies more than in the background. In this paper, we propose a new approach for vehicle license plate localization using an optimal trade-off maximum average correlation height (TO-MACH) filter in the frequency domain...
In many chemical industries, the metallurgy, a number of digital real-time monitoring instruments are used. The manual method will bring the problems of inefficient and misjudge. To recognize digital display instrument's real-time reading, a BP neural network is designed, an improved BP algorithm and fifteen feature extraction method is proposed. The image of instrument board is obtained by an digital...
Automatically assigning relevant text keywords to images is an important problem. Many algorithms have been proposed in the past decade and achieved good performance. Efforts have focused upon model representations of keywords, but properties of features have not been well investigated. In most cases, a group of features is preselected, yet important feature properties are not well used to select...
One of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the edge of image where the preciseness and reliability of its results will affect directly the comprehension machine system made for objective world. Several edge detectors have been developed in the past decades, although no single edge detectors have...
This paper represents a currency recognition system using ensemble neural network (ENN). The individual neural networks (NN) in an ENN are trained via negative correlation learning. The object of using negative correlation learning (NCL) is to expertise the individuals in an ensemble on different parts or portion of input patterns. The available currencies in the market consist of new, old and noisy...
In this work, we present a new approach for optimum design of nonlinear filters based on support vector machines. Taking advantage on the general concept of binary filters and machine learning theory, this proposed approach, is based on the concept of a new filter structured, called support vector machine filter (SVMF) and statistical data analysis. This proposed filter approach, is used as an impulsive...
This paper presents a new approach to image restoration based on ANN, considering the learning of the inverse process using a standard image for training under a multiscale approach. Different models of ANN were tested and compared with the traditional techniques. The standard image was artificially degraded to simulate some types of frequent degradation problems. Due to the huge amount of data generated...
This paper introduces a class of correlation filters called average of synthetic exact filters (ASEF). For ASEF, the correlation output is completely specified for each training image. This is in marked contrast to prior methods such as synthetic discriminant functions (SDFs) which only specify a single output value per training image. Advantages of ASEF training include: insensitivity to over-fitting,...
As an important image feature, a corner takes significant position in camera calibration, pattern recognition and image matching area. A large amount of image corner points are the intersecting points of the edges of polygons. A corner point extracting method based on support vector for regression (SVR) was proposed aimed at extracting intersecting points. First, a digital image of geometric figures...
This paper presents PWEM, a technique for detecting class label noise in training data. PWEM detects mislabeled examples by assigning to each training example a probability that its label is correct. PWEM calculates this probability by clustering examples from pairs of classes together and analyzing the distribution of labels within each cluster to derive the probability of each label's correctness...
Image segmentation is a fundamental issue in image processing. Segmentation of synthetic aperture radar (SAR) images is extremely difficult on account of intrinsic multiplicative speckle noises. Due to the ambiguities of SAR images, labeled instances are difficult and time-consuming to obtain while unlabeled data are abundant. In this paper, a new semi-supervised approach based on transductive support...
One of the most research challenges in image processing is image enhancement and reducing impulse noise from digital images. There are various methods for impulse noise reduction such as median based filters or nonlinear filters, but these methods more or less cause images to blur and to remove important details from images, as in high noise ratio in that noise reduction will destroy vital information...
In this Paper we have presented a Fingerprint verification system based on hybrid approach which combines both the Feature extraction by applying a set of different wavelet families (functions) and minutiae information available in the fingerprint image by fusion rule method. The Core Point (CP) of the input Fingerprint is detected. Keeping the CP in the center,the image of size w x w is cropped and...
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