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A sign language recognition system is an attempt to bring the speech and the hearing impaired community closer to more regular and convenient forms of communication. Thus, this system requires to recognize the gestures from a sign language and convert them to a form easily understood by the hearing. The model that has been proposed in this paper recognizes static images of the signed alphabets in...
In this paper, we propose an emotion-based feature fusion method using the Discriminant-Analysis of Canonical Correlations (DCC) for facial expression recognition. There have been many image features or descriptors proposed for facial expression recognition. For the different features, they may be more accurate for the recognition of different expressions. In our proposed method, four effective descriptors...
PCANet was proposed as a lightweight deep learning network that mainly leverages Principal Component Analysis (PCA) to learn multistage filter banks followed by binarization and block-wise histograming. PCANet was shown worked surprisingly well in various image classification tasks. However, PCANet is data-dependence hence inflexible. In this paper, we proposed a data-independence network, dubbed...
The Data Encryption Standard (DES) was a prevalent symmetric key block cipher scheme. It was the most popular used cryptographic algorithm. DES's security was a highly debatable aspect until it became an insecure algorithm in 1999. In this paper, an enhancement that overcomes the security weakness of DES is introduced. The modification employs the chaotic logistic map and the art of the Elliptic Curve...
Affect recognition is an inherently multi-modal task that makes it appealing to investigate classifier combination approaches in real world scenarios. Thus a variety of different independent classifiers can be constructed from basically independent features without having to rely on artificial feature views. In this paper we study a large variety of fusion approaches based on a multitude of features...
Recently, steganalysis based on hypothesis test theory becomes a focus. However, the correlation between adjacent pixels is not exploited and this is obviously not reasonable. In this paper, a new detector for least significant bit matching (LSBM) steganography is proposed with the consideration of pixel correlation. The cover pixels are modeled by multivariate Gaussian distribution and a new detector...
Multimedia information security has a vital role in communication systems. One of the security aspects is the encryption. A new image encryption approach, that uses the Camellia block cipher algorithm combined with the logistic chaotic map, is proposed in this paper. CAT map is used to scramble the image and the S-function output is masked for more security. Key schedule algorithm is used to generate...
Rumormongers always use long paragraphs to spread slanderous stories so that they can convince readers. Those illegal or sensitive rumors uploaded into the internet can be written on images to by-pass text filters. These images can be detected by existing filters such as OCR, but the detection is very time consuming. To prohibit the dissemination of those commentaries, detecting whether an image contains...
Cognitive growth of computer communication lead to radical improvement in wireless technology and shrunken the world into palms of user. During storing and sharing, avoiding third party access of data is a challenge. Image encryption is a popular technique widely used in the present scenario to protect secret information. Encryption achieves this by converting original data into unintelligible form...
High Efficiency Video Coding (HEVC) is a novel video compression standard. It provides significantly better performance than its predecessor, but introduces high computational complexity due its hierarchical block structure. Determining Coding Units (CU), Prediction Units (PU), and Transform Units (TU) size is a time consuming process, as block partitioning decisions are based on rate-distortion optimization...
In this paper, we propose a new neighborhood repulsed correlation metric learning (NRCML) method for kinship verification. While several metric learning algorithms have been proposed in recent years and some of them have successfully applied to kinship verification, most existing metric learning methods are developed based on the Euclidian similarity metric, which is not powerful enough to measure...
Due to the popularity of multimedia technology and digital world, thousands of videos are accessed through internet in seconds. Most of the videos, available in internet for public access are non-edited videos. Efficient way of searching and storage need an efficient method of annotation. Automatic cut detection is the first stage of any automatic annotation process. In this paper we addressed the...
It is well know that a measure of contrast in images is not yet fully defined. The conventional measures of contrast consist of global computations and therefore they have a poor performance. At the same time image quality assessment is often based on quantifying the visibility between a structure of interest or foreground and its surrounding background, i.e., the contrast ratio. Then, a high quality...
The performance of a biometric recognition algorithm is often evaluated by testing it on standard datasets. This process, known as technology evaluation, is necessary to compare the matching performance of different algorithms. In the case of iris recognition, datasets such as ICE, MBGC, CASIA, NICE, WVU, UBIRIS, etc. have been used for this purpose. However, iris images in each of these datasets...
In the process of 3D regeneration from stereo images, a disparity map can be determined by matching the same objects on the stereo image pair. However, different light conditions of an image pair, such as exposure, illumination, and illuminant color, usually compromise the accuracy of matching. This usually occurs when taking outdoor images. In this paper, we propose a preprocessing method to improve...
Achieving high accuracy for classifying foreground and background is an interesting challenge in the field of scene image analysis because of the wide range of illumination, complex background, and scale changes. Classifying foreground and background using bag-of-feature model gives a good result. However, the performance of the classifier depends on designed features. Therefore, this paper presents...
Presently, in digital scenario, the most prime requirement is to secure data while transmitting through communication channel. Commonly, cryptography and steganography are used to achieve this purpose. In this work, we propose a novel spatial domain image steganography by converting the pixel intensity value into Triangular base. Our algorithm is capable of hiding 8 bits per pixel of an image component...
Robust object tracking is a challenging computer vision problem due to dynamic changes in object pose, illumination, appearance and occlusions. Tracking objects between frames requires accurate matching of their features. We investigate real time matching of mobile object features for frame to frame tracking. This paper presents a new feature matching approach between objects for tracking that incorporates...
The bag-of-visual-words model has been widely utilized for content based image and video retrieval due to its scalability. In this paper, we extend this model for human action video retrieval. We adopt dense trajectory features which are able to achieve the state-of-the-art performance on action recognition, while most of the existing video retrieval methods utilize descriptors of local interest points...
We investigated effective features for human detection. The histogram of oriented gradients (HOG), which was proposed by N. Dalal, is an important representation that accumulates the edge-magnitude into a quantized histogram. Effective features similar to the HOG have been proposed. We question what the most effective feature is. We thus evaluate several features on three datasets of pedestrians,...
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