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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...
Now a days, a great attention has received for content-based image retrieval by the researchers. It is very popular and interesting topic of computer vision. The basic requirement of content based image retrieval is to extract the appropriate information from the large image repository corresponding to query image on the basis of contents with better system performance. But, in the development of...
An Image Retrieval (IR) system is used for accessing and retrieving the images from large image database. Content means the image features like color, texture and shape of the image. For Color feature, it is scaling and rotation invariant. It encrypts the color data they are a good component to use under changing lighting conditions. Three color moments are figured per channel (e.g. 6 minutes if the...
The images of distant view and close-up view indicate a photographers' attention which can be further utilized for user behavior analysis and scene evaluation. As images may compose arbitrary contexts, distant view and close-up view classification becomes non-trivial. In this work, we found two cues can represent human visual attention, i.e. focus cue and scale cue. We model the focus cue in frequency...
In this paper, we propose a new secure content based image retrieval (SCBIR) system adapted to the cloud framework. This solution allows a physician to retrieve images of similar content within an outsourced and encrypted image database, without decrypting them. Contrarily to actual CBIR approaches in the encrypted domain, the originality of the proposed scheme stands on the fact that the features...
Content based image retrieval helps manipulators to retrieve pertinent images based on their contents. A consistent content-based feature extraction technique is required to meritoriously extract most of the information from the images. These important elements include color, texture, intensity or shape of the object inside image. Various descriptors required for extracting global and local features...
An iris is unique physiological biometric trait compared to other biological traits to authenticate a person. In this paper we propose straight line fusion based iris recognition using Adaptive Histogram Equalization (AHE), Histogram Equalization (HE) and Discrete Wavelet Transform (DWT). The CASIA V.I iris database is considered and horizontal iris template is generated in the pre-processing. The...
In image processing research field, image retrieval is extensively used in various application. Increasing need of the image retrieval, it is quiet most exciting research field. In image retrieval system, features are the most significant process used for indexing, retrieving and classifying the images. For computer systems, automatic indexing, storing and retrieving larger image collections effectively...
The human ear is a new technology in biometrics which is not yet used in a real context or in commercial applications. For this purpose of biometric system, we present an improvement for ear recognition methods that use Elliptical Local Binary Pattern operator as a robust technique for characterizing the fine details of the two dimensional ear images. The improvements are focused on feature extraction...
In this paper, a feature extraction method based on Dual Tree Complex Wavelet Transform (DTCWT) domain has been proposed to classify left and right hand motor imagery movements from electroencephalogram (EEG) signals. After first performing auto-correlation of the EEG signals to reduce noise and enhance the weak brain signals, the EEG signals are decomposed into several bands of real and imaginary...
In this paper, Dual Tree Complex Wavelet Transform (DTCWT) domain based feature extraction method has been proposed to identify left and right hand motor imagery movements from electroencephalogram (EEG) signals. After first performing auto-correlation of the EEG signals to enhance the weak brain signals and reduce noise, the EEG signals are decomposed into several bands of real and imaginary coefficients...
The popular Local binary patterns (LBP) have been highly successful in describing and recognizing faces. However, the original LBP has several limitations which must to be optimized in order to improve its performances to make it suitable for the needs of different types of problems. In this paper, we investigate a new local texture descriptor for automated human identification using 2D facial imaging,...
Brain-computer interfaces (BCIs) require real-time feature extraction for translating input EEG signals recorded from a subject into an output command or decision. Owing to the inherent difficulties in EEG signal processing and neural decoding, many of the feature extraction algorithms are complex and computationally demanding. Presently, software does exist to perform real-time feature extraction...
Content based image retrieval is grievous need of present scenario in digital imaging world. This work presents a new multi-scale content based image retrieval system which leverages the multi-resolution property of discrete wavelet transform (DWT) and the local information attribute of local extrema patterns (LEPs). Two level DWT is applied on images and wavelet coefficients are obtained for images,...
Magnetic resonance spectroscopic imaging (MRSI) integrates spectroscopic and imaging methods to acquire spatially localized spectra associated with a specific patient. MRSI is a relatively new imaging entity for clinical applications and gathering relevant data is an expensive task. Therefore, only few small databases might exist for clinical use. However, the rapid advances made in the field of NMR...
In this letter, analyze the satellite images by using discrete cosine transform and singular value decomposition. The proposed technique presents an advance multiband satellite colour, contrast improvement technique of a poor-contrast satellite images. The input image is decomposed into the two frequency sub bands by using DCT and estimates the singular value matrix of the lowâ"low...
Covert Communication using digital images is rapidly gaining popularity. It alters some of the image properties that may introduce few degradation or unusual characteristics. These characteristics may act as signatures that broadcast the existence of the embedded message and thus defeating the purpose of steganography. With large number of techniques being developed in image steganography, universal...
Content based Image Retrieval (CBIR) allows automatically extracting target images according to objective visual contents of the image itself. Representation of visual features and similarity match are important issues in CBIR. Colour and texture features are important properties in CBIR systems. In this paper, a combined feature descriptor for CBIR is proposed to enhance the retrieval performance...
Vehicle license plate identification system is an image-processing technology used to identify vehicles by their license plates. This technology is used in various security and traffic applications. This data is also used for enforcement, data collection, and can be used to keep a time record on the entry or exit of vehicles for automatic payment calculations. The significant advantage of this system...
This paper introduces a cepstral approach for the detection of landmines from acoustic images. This approach is based on transforming the 2D landmine images to 1D signals using a spiral scan to make object pixels as close as possible to each other after the scan. The Mel-frequency cepstral coefficients (MFCCs) and polynomial shape coefficients are extracted from these 1D signals to form a database...
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