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Fault diagnosis of roller bearings in rotating machinery is of great significance to identify latent abnormalities and failures in industrial plants. This paper presents a new self-adaptive fault diagnosis system for different conditions of roller bearings using InfraRed Thermography (IRT). In the first stage of the proposed system, 2-Dimensional Discrete Wavelet Transform (2D-DWT) and Shannon entropy...
This paper studies the segmentation methods by analyzing the threshold method of rubbings. Firstly, OTSU and fast 2 dimensional OTSU threshold segmentation algorithms are presented, and the segmentation effect of a given image is analyzed. The limitation of OTSU, and fast 2 dimensional OTSU segmentation algorithm are explained. Then the segmentation algorithm is given in conjunction with the histogram,...
It is widely accepted that feature extraction is quite possibly the most critical step in computer vision. Typically, feature extraction is performed using a method such as the histogram of oriented gradients. In recent years, a shift has occurred from human to machine learned features, e.g., convolutional neural networks (CNNs) and Evolution-COnstructed (ECO) features. An advantage of our improved...
LBP coefficients are essential and determine the priority of gray differences. The objectives of this paper are to reveal this and propose a method for finding an optimal priority through the genetic algorithm. On the other hand, the genetic operators such as initialization and cross-over operators, generate invalid coefficients, defective chromosomes. This paper also recommends a rectifying method...
In this paper, we propose an effective mixed method approach for classification of brain tumor tissues. Here proposed system will be using Genetic Algorithm for feature Extraction and Support Vector machine for classification. These features are compared with stored features. Feature extraction is a method used to capture visual content of the image. The feature extraction is the method to signify...
Image classification is a crucial task in Computer Vision. Feature detection represents a key component of the image classification process, which aims at detecting a set of important features that have the potential to facilitate the classification task. In this paper, we propose a Genetic Programming (GP) approach to image feature detection. The proposed method uses the Speeded Up Robust Features...
This research is addresses to determine the dominant species that located in the overlapped clusters produced by the Kohonen Self-Organizing Map (KSOM). Before, KSOM algorithm able to cluster the tropical wood species data set effectively and accurately according to the wood features, which is wood pores sizes. Unfortunately, there are seven overlapped clusters in the clustering result and this is...
This paper discusses the performance evaluation of the Content Based Image Retrieval (CBIR) system using the optimality in selection of feature vector elements. The performance of the CBIR system may be improved by appropriate analysis of the image. Image analysis is still facing problems related to the detection of the objects. In spite of the noticeable achievements using the part based model, the...
In this paper, we propose the optimal parameters of local binary patterns such as type of pattern, size of blocks in the feature space and distance measure for face recognition using a genetic algorithm. The genetic algorithm is able to optimize all these parameters quickly and to improve the recognition accuracy. We provide a comparative study of three types of local binary patterns (LBP, LGP and...
In this paper, we demonstrate how neurogenetic reconstruction can be used to reconstruct facial images from biometric templates extracted using Local Binary Patterns (LBPs). We also demonstrate the process of neurogenetic distortion of biometric templates in order to mitigate neurogenetic reconstruction. Our results show that reconstructed images can be used to recognize individuals within a dataset...
Palmprint identification is a subcategory of biometrics identification, which can be efficiently used to identify the people. Palmprint-based identification is currently a potential alternative to human identification method of a well known fingerprint-based identification. For example, if the hand of the identified person is dirty, the accuracy of fingerprint-based identification is distorted, while...
Steganalytic techniques are used to detect whether an image contains a hidden message. By analyzing different image features between stego-images (the image within which information is hidden) and cover-images (the image in which information is to be hidden), a steganalytic system is able to detect stego-images. In this paper, we present a new method in LSB embedding by avoiding the change of statistic...
Given an image from a biometric sensor, it is important for the feature extraction module to extract an original set of features that can be used for identity recognition. This form of feature extraction has been referred to as Type I feature extraction. For some biometric systems, Type I feature extraction is used exclusively. However, a second form of feature extraction does exist and is concerned...
One of the most important modules of any bio-metric system is the feature extraction module. Given a sample it is important for the feature extraction method to extract a rich set of features that can be used for identity recognition. This form of feature extraction has been referred to as Type I feature extraction and for some biometric systems it is used exclusively. However, a second form of feature...
With the development of computer aided design technique,3D reconstruction from 2D input has been widely used in the research of computer vision. Plentiful works have been done in three orthographic views, in this paper a new method is introduced under single 2D input. The system in this paper aims at the reconstruction of useful objects in computer design. Angle histogram and corner detector are used...
In this study, a new feature-based steganalytic method is presented and four classification methods: Fisher linear discriminant, Gaussian naive Bayes, multilayer perceptron, and k nearest neighbor, are compared for steganalysis of suspicious images. The method exploits statistics of the histogram, wavelet statistics, amplitudes of local extrema from the ID and 2D adjacency histograms, center of mass...
Based on the histogram invariant moments and Genetic Algorithms, a new remote sensing image matching method is developed to provide robust matching between the remote sensing images having a change in rotation or scale. Image pyramid technology is integrated into the Genetic Algorithms to provide an effective and robust search order. Histogram invariant moment which is invariant to rotation is used...
A parallel genetic algorithm (PGA) based scheme for detection of cracks in images is proposed. The proposed segmentation scheme is a feature based one and the optimum threshold is determined from the the feature histogram. Parallel genetic algorithm (PGA) based clustering is proposed to detect two peaks and thereafter the optimal threshold is determined by minimum mean square error (MMSE) based strategy...
A mechanism involving evolutionary genetic programming (GP) and the expectation maximization algorithm (EM) is proposed to generate feature functions automatically, based on the primitive features, for an image pattern recognition system on the diagnosis of the disease OPMD. Prior to the feature function generation, we introduce a novel technique of the primitive texture feature extraction, which...
Content based image retrieval (CBIR) systems aim to provide a means to find pictures in large repositories without using any other information except its contents usually as low-level descriptors. Since these descriptors do not exactly match the high level semantics of the image, assessing perceptual similarity between two pictures using only their feature vectors is not a trivial task. In fact, the...
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