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There is always noise inside the digital images. Noise is an unwanted component of the image. The existence of noise in a face image can degrade the accuracy of a face recognition. Therefore, we need a proper method that can cope noise or restore the quality of the image. The best method to overcome noise in the image is to use smoothing (filter). In this research, we discuss some techniques to overcome...
In this paper we concentrate our efforts on the analysis of the facial landmarks dynamics as being a relevant method to access the subject's emotion. Given the person's facial landmarks we describe their trajectory with respect to the neutral pose and out of this trajectory we extract relevant features that are subsequently entered into a classification system for the actual recognition of emotion...
Security of published data cannot be less important as compared to unpublished data or the data which is not made public. Therefore, PII (Personally Identifiable Information) is removed and data sanitized when organizations recording large volumes of data publish that data. However, this approach of ensuring data privacy and security can result in loss of utility of that published data for knowledge...
t-Closeness was introduced as an improvement of the well-known k-anonymity privacy model for data release. On the other hand, e-differential privacy was originally proposed as a privacy property for answers to on-line database queries and it has been very welcome in academic circles. In spite of their quite diverse origins and motivations, we show in this paper that t-closeness and e-differential...
This paper proposes a robust TV advertisement search based on audio fingerprinting in real environments. To obtain prominent audio peak pairs against different types of distortions, an adaptive thresholding method based on a median filter and peak-picking update is applied. Using the prominent audio peak-pair hashing, the proposed audio fingerprinting algorithm improves the robustness of the TV advertisement...
Electrocardiogram (ECG) is a biological signal which reflects the electronic excitement of cardiac activities and vital signs. As a kind of signal time marker, the parameter information of ECG, such as R wave amplitude and RR period, plays an important part in clinic. According to the traditional characteristics of ECG signal, an ECG automatic analysis system is designed based on virtual instruments...
We present an optimization framework that solves constrained multi-agent optimization problems while keeping each agent's state differentially private. The agents in the network seek to optimize a local objective function in the presence of global constraints. Agents communicate only through a trusted cloud computer and the cloud also performs computations based on global information. The cloud computer...
Many democratic countries choose their representatives through electronic elections. Even being a modern tool, its results can be explored maliciously. Because that, many instruments and protocols are using to protect electronic elections from attacks. This work propose a new system to improve the security in electronic elections. It is based on analyses of behavior voter to detect urns with dissonant...
Diabetic retinopathy (DR), a complication due to diabetes, is the leading cause of blindness. Diagnosis of DR at its earliest is thus very necessary. In this paper, we present an automated computer aided method for detection of hemorrhages using fundus images. In the first stage, blood vessel (BV) is detected and eliminated. In the following stage hemorrhage candidate is detected. The method is applied...
Nowadays, more and more activity recognition algorithms begin to improve recognition performance by combining the RGB and depth information. Although, the space-time volumes (STV) algorithm and the space-time local features algorithm can combine the RGB and depth information effectively, they also have their own defects. Such as they need expensive computational cost and they are not suitable for...
Deep convolutional networks have recently shown very interesting performance in a variety of computer vision tasks. Besides network architecture optimization, a key contribution to their success is the availability of training data. Network training is usually done with manually validated data but this approach has a significant cost and poses a scalability problem. Here we introduce an innovative...
Arc faults in photo-voltaic (Pv) systems are dangerous events and can create huge damage. In order to decrease the number of these events, arc fault detectors are used. The advantages of the here presented detection algorithm are the relatively low computational demand and the ability to work with most standard analog-digital converter (Adc) contained in micro controllers.
This paper provides a novel and unified framework of representation based classification technique. The proposed atomic representation based classification (ARC) framework includes, but not limited to, sparse representation based classification (SRC), low-rank representation based classification (LRRC) as special cases. Despite good performance, most existing classification methods are heavily reliant...
The orientation field of a fingerprint is crucial for feature extraction and matching. However, estimation of orientation fields in latents is very challenging because latents are usually of poor quality. Inspired by the superiority of convolutional neural networks (ConvNets) for various classification and recognition tasks, we pose latent orientation field estimation in a latent patch to a classification...
Significant improvement in no-reference image quality assessment (NR-IQA) methods has been demonstrated in recent years. The demonstrated prediction performance of proposed NR-IQA methods, in terms of correlations between predicted and subjective scores, has reached similar performance levels with full-reference image quality assessment (FR-IQA) measures, on popular image datasets. However, in our...
Finger vein is a new and promising trait in biometric recognition and some related progress have been achieved in recent years. Considering that there are many different sensors in a biometric system, sensor interoperability is a very important issue and still neglected in the state-of-the-art finger vein recognition. Based on the analysis of the shortcomings in the current finger vein ROI extraction...
The appearance of masses in in X-ray mammograms is one of the early signs of women breast cancer. Currently, mammography is the single most effective and reliable technique in the investigation of breast abnormalities detection such as masses. However, their detection is still a challenging problem due, to the diversity in shape, size, ambiguous margins and to the poor contrast between the cancerous...
Current concerns about data privacy have lead to increased focus on data anonymization methods. Differential privacy is a new mechanism that offers formal guarantees about anonymization strength. The main challenge when using differential privacy consists in the difficulty in designing correct algorithms when operating on complex data types. One such data type is sequential data, which is used to...
Privacy is an increasing concern as the number of databases containing personal information grows. Differential privacy algorithms can be used to provide safe database queries through the insertion of noise. Attackers cannot recover pieces of the initial data with certainty, but this comes at the cost of data utility. Noise insertion leads to errors, and signal to noise ratio can become an issue....
The mainstream approach to image quality assessment has centered around accurately modeling the single most relevant strategy employed by the human visual system (HVS) when judging image quality. In this work, it suggest that a single strategy used for single database may not be sufficient; rather, The no-reference/blind image quality assessment (NR-IQA) is the most difficult due to the reference...
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