[show abstract][hide abstract] ABSTRACT: Automated human identification is a significant issue in real and virtual societies. Iris is a suitable choice for meeting this goal. In this paper, we present an iris recognition system that uses images acquired in both near-infrared and visible lights. These two types of images reveal different textural information of the iris tissue. We demonstrated the necessity to process both VL and NIR images to recognize irides. The proposed system exploits two feature extraction algorithms: one is based on 1D log-Gabor wavelet which gives a detailed representation of the iris region and the other is based on 1D Haar wavelet which represents a coarse model of iris. The Haar wavelet algorithm is proposed in this paper. It makes smaller iris templates than the 1D log-Gabor approach and yet achieves an appropriate recognition rate. We performed the fusion at the match score level and examined the performance of the system in both verification and identification modes. UTIRIS database was used to evaluate the method. The results were compared with other approaches and proved to have better recognition accuracy, while no image enhancement technique is utilized prior to the feature extraction stage. Furthermore, we demonstrated that fusion can compensate the lack of input image information, which can be beneficial in reducing the computation complexity and handling non-cooperative iris images.
Machine Vision and Applications 11/2013; · 1.10 Impact Factor
[show abstract][hide abstract] ABSTRACT: This paper presents a novel and uniform framework for face recognition. This framework is based on a combination of Gabor wavelets, direct linear discriminant analysis (DLDA) and support vector machine (SVM). First, feature vectors are extracted from raw face images using Gabor wavelets. These Gabor-based features are robust against local distortions caused by the variance of illumination, expression and pose. Next, the extracted feature vectors are projected to a low-dimensional subspace using DLDA technique. The Gabor-based DLDA feature vectors are then applied to SVM classifier. A new kernel function for SVM called hyperhemispherically normalized polynomial (HNP) is also proposed in this paper and its validity on the improvement of classification accuracy is theoretically proved and experimentally tested for face recognition. The proposed algorithm was evaluated using the FERET database. Experimental results show that the proposed face recognition system outperforms other related approaches in terms of recognition rate.
[show abstract][hide abstract] ABSTRACT: In our previous work, “robust transmission of scalable video stream using modified LT codes”, an LT code with unequal packet protection property was proposed. It was seen that applying the proposed code to any importance-sorted input data, could increase the probability of early decoding of the most important parts when enough number of encoded symbols is available at the decoder’s side. In this work, the performance of the proposed method is assessed in general case for a wide range of loss rate, even when there are not enough encoded symbols at the decoder’s side. Also in this work the degree distribution of input nodes is investigated in more detail. It is illustrated that sorting input nodes in encoding graph, as what we have done in our work, has superior advantage in comparison with unequal input node selection method that is used in traditional rateless code with unequal error protection property.
[show abstract][hide abstract] ABSTRACT: The objective of image fusion is to combine relevant information from multiple images into a single image. The discrete cosine transform (DCT) based methods of image fusion are more efficient and time-saving in real-time systems using DCT based standards of still image or video. Existing DCT based methods are suffering from some undesirable side effects like blurring or blocking artifacts which reduce the quality of the output image. Furthermore, some of these methods are rather complex and this contradicts the concept of the simplicity of DCT based algorithms. In this paper, an efficient approach for fusion of multi-focus images based on variance calculated in DCT domain is presented. Due to simplicity of our proposed method, it can be easily used in real-time applications. The experimental results verify the efficiency improvement of our method both in output quality and complexity reduction in comparison with several recent proposed techniques.
[show abstract][hide abstract] ABSTRACT: In this paper we propose a multi sensor tracking method. Tracking is done independently for each view. Fusing several cues including color, edge, texture and motion constrained by structure of environment is used in a novel way and in particle filter framework. The results of individual image planes are projected to ground plane using homography relation. The similarity of projected locations with the reference model and minimum variance estimate are two key points to evaluate the location of the target. Also, we introduce a method based on two views tracking to handle occlusion. Robust statistic is used to declare an occlusion in one view. Homography relation and inter-frame transformation are the tools to cancel the occlusion. Experimental results show the robustness and accuracy of the proposed method.
[show abstract][hide abstract] ABSTRACT: The widespread usage of image fusion causes an increase in the importance of assessing the performance of different fusion algorithms. The problem of introducing a suitable quality measure for image fusion lies in the difficulty of defining an ideal fused image. In this paper, we propose a non-reference objective image fusion metric based on mutual information which calculates the amount of information conducted from the source images to the fused image. The considered information is represented by image features like gradients or edges, which are often in the form of two-dimensional signals. In this paper, a method of estimating the joint probability distribution from marginal distributions is also presented which is employed in calculation of mutual information. The proposed method is compared with the most popular existing algorithms. Various experiments, performed on several databases, certify the efficiency of our proposed method which is more consistent with the subjective criteria.
[show abstract][hide abstract] ABSTRACT: LT codes are convenient and popular kind of rateless codes that could easily tolerate different patterns of loss in erasure channels. In this paper an LT code with unequal packet protection (UPP) property is proposed. The proposed code could provide unequal packet recovery to any importance-sorted data packets. Simulation results indicate the enhanced performance of the suggested scheme and its ability to increase the probability of early decoding of more important parts of data rather than the rest. Also it is shown that the proposed scheme could provide comparable bit error rates in comparison to the one of the well known previous methods. The code with modified encoding graph has been utilized for transmitting of the scalable data-partitioned video stream. Simulation results also illustrate the performance of the suggested approach in early delivery of the most important parts of a video sequence.
[show abstract][hide abstract] ABSTRACT: v The transmission of block-coded images over wireless channels results in lost blocks. In this paper, we propose a new error concealment method for covering up the high packet losses of an original image after its transmission through an error- prone channel. In this scheme, Discrete Wavelet Transform (DWT) is applied to each block of the original image in order to produce a lower resolution copy of the each block. Then, we choose approximation coefficients of each block as replica of the block and embed it into a remote block of the image in the spatial domain. It is shown that the proposed scheme provides significant improvement over existing algorithms in terms of both subjective and objective evaluations. This technique can be implemented for wireless channels to combat degradations in a backward-compatible scheme. Keywordsr Error concealment; Image transmission; Watermarking; Wireless channels.
[show abstract][hide abstract] ABSTRACT: Object Tracking using mean shift algorithm has gained much attention in recent years due to its simplicity. In this paper, we present a modified mean shift tracking method using genetic algorithm. First, a background elimination method is used to eliminate the effects of the background on the target model. The mean shift procedure is applied only for one iteration to give a good approximate region of the target. In the next step, the genetic algorithm is used as a local search tool to exactly identify the target in a small window around the position obtained from the mean shift algorithm. The simulation results prove that the proposed method outperforms the traditional mean shift algorithm in finding the precise location of the target at the expense of slightly more complexity.
[show abstract][hide abstract] ABSTRACT: In this paper, we present an effective and robust visual vehicle tracking algorithm using particle filter and multiple cues. A stable histogram-based framework is extended to evaluate color, edge, texture and motion cues in structured environments. This framework is suitable for practical conditions since in many applications the object motions are limited by structure of the surveillance scene. We show the appropriate method to model the likelihood function of each cue. However motion cue is irregular, so generating the corresponding distribution from its likelihood function and using the structure of environment as likelihood decision function can handle this problem. For modeling the environment, distance transform is used. In addition, noise parameters and the fusing weight of cues are obtained adaptively. Experimental results on several video surveillance sequences show the effectiveness and robustness of proposed method.
[show abstract][hide abstract] ABSTRACT: In this paper we propose a multi sensor tracking method. Tracking is done independently for each view. Fusing several cues including color, edge, texture and motion constrained by structure of environment is used in a novel way. Fusion of features in particle filter framework helps to achieve an accurate tracking algorithm in single view. The results of individual image planes are projected to the ground plane using homography relation. The similarity of the projected locations with the reference model and minimum variance estimate are two key points to evaluate the total location of the target. Experimental results show the robustness and accuracy of the proposed method.