Reza Azad

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Teacher Assistant, Machine Learning at Sharif University of Technology

  • Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions

    In recent years, deep learning-based networks have achieved state-of-the-art performance in medical image segmentation. Among the existing networks, U-Net has been successfully applied on medical image segmentation. In this paper, we propose an extension of U-Net, Bi-directional ConvLSTM U-Net with Densely connected convolutions (BCDU-Net), for medical image segmentation, in which we take full advantages of U-Net, bi-directional ConvLSTM (BConvLSTM) and the mechanism of dense convolutions. Instead of a simple concatenation in the skip connection of U-Net, we employ BConvLSTM to combine the feature maps extracted from the corresponding encoding path and the previous decoding up-convolutional layer in a non-linear way. To strengthen feature propagation and encourage feature reuse, we use densely connected convolutions in the last convolutional layer of the encoding path. Finally, we can accelerate the convergence speed of the proposed network by employing batch normalization (BN). The proposed model is evaluated on three datasets of: retinal blood vessel segmentation, skin lesion segmentation, and lung nodule segmentation, achieving state-of-the-art performance.

    08/31/2019 ∙ by Reza Azad, et al. ∙ 54 share

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  • Real-Time and Robust Method for Hand Gesture Recognition System Based on Cross-Correlation Coefficient

    Hand gesture recognition possesses extensive applications in virtual reality, sign language recognition, and computer games. The direct interface of hand gestures provides us a new way for communicating with the virtual environment. In this paper a novel and real-time approach for hand gesture recognition system is presented. In the suggested method, first, the hand gesture is extracted from the main image by the image segmentation and morphological operation and then is sent to feature extraction stage. In feature extraction stage the Cross-correlation coefficient is applied on the gesture to recognize it. In the result part, the proposed approach is applied on American Sign Language (ASL) database and the accuracy rate obtained 98.34

    08/08/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • Real-Time Human-Computer Interaction Based on Face and Hand Gesture Recognition

    At the present time, hand gestures recognition system could be used as a more expected and useable approach for human computer interaction. Automatic hand gesture recognition system provides us a new tactic for interactive with the virtual environment. In this paper, a face and hand gesture recognition system which is able to control computer media player is offered. Hand gesture and human face are the key element to interact with the smart system. We used the face recognition scheme for viewer verification and the hand gesture recognition in mechanism of computer media player, for instance, volume down/up, next music and etc. In the proposed technique, first, the hand gesture and face location is extracted from the main image by combination of skin and cascade detector and then is sent to recognition stage. In recognition stage, first, the threshold condition is inspected then the extracted face and gesture will be recognized. In the result stage, the proposed technique is applied on the video dataset and the high precision ratio acquired. Additional the recommended hand gesture recognition method is applied on static American Sign Language (ASL) database and the correctness rate achieved nearby 99.40 the planned method could be used in gesture based computer games and virtual reality.

    08/07/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • New Method for Optimization of License Plate Recognition system with Use of Edge Detection and Connected Component

    License Plate recognition plays an important role on the traffic monitoring and parking management systems. In this paper, a fast and real time method has been proposed which has an appropriate application to find tilt and poor quality plates. In the proposed method, at the beginning, the image is converted into binary mode using adaptive threshold. Then, by using some edge detection and morphology operations, plate number location has been specified. Finally, if the plat has tilt, its tilt is removed away. This method has been tested on another paper data set that has different images of the background, considering distance, and angel of view so that the correct extraction rate of plate reached at 98.66

    07/24/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • Novel and Tuneable Method for Skin Detection Based on Hybrid Color Space and Color Statistical Features

    Skin detection is one of the most important and primary stages in some of image processing applications such as face detection and human tracking. So far, many approaches are proposed to done this case. Near all of these methods have tried to find best match intensity distribution with skin pixels based on popular color spaces such as RGB, CMYK or YCbCr. Results show these methods cannot provide an accurate approach for every kinds of skin. In this paper, an approach is proposed to solve this problem using statistical features technique. This approach is including two stages. In the first one, from pure skin statistical features were extracted and at the second stage, the skin pixels are detected using HSV and YCbCr color spaces. In the result part, the proposed approach is applied on FEI database and the accuracy rate reached 99.25 + 0.2. Further proposed method is applied on complex background database and accuracy rate obtained 95.40+0.31 all kinds of skin using train stage which is the main advantages of it. Low noise sensitivity and low computational complexity are some of other advantages.

    07/24/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • A Robust and Efficient Method for Improving Accuracy of License Plate Characters Recognition

    License Plate Recognition (LPR) plays an important role on the traffic monitoring and parking management. A robust and efficient method for enhancing accuracy of license plate characters recognition based on K Nearest Neighbours (K-NN) classifier is presented in this paper. The system first prepares a contour form of the extracted character, then the angle and distance feature information about the character is extracted and finally K-NN classifier is used to character recognition. Angle and distance features of a character have been computed based on distribution of points on the bitmap image of character. In K-NN method, the Euclidean distance between testing point and reference points is calculated in order to find the k-nearest neighbours. We evaluated our method on the available dataset that contain 1200 sample. Using 70 for training, we tested our method on whole samples and obtained 99 recognition rate.Further, we achieved average 99.41 three/strategy validation technique on 1200 dataset.

    07/24/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • Real-Time and Efficient Method for Accuracy Enhancement of Edge Based License Plate Recognition System

    License Plate Recognition plays an important role on the traffic monitoring and parking management. Administration and restriction of those transportation tools for their better service becomes very essential. In this paper, a fast and real time method has an appropriate application to find plates that the plat has tilt and the picture quality is poor. In the proposed method, at the beginning, the image is converted into binary mode with use of adaptive threshold. And with use of edge detection and morphology operation, plate number location has been specified and if the plat has tilt; its tilt is removed away. Then its characters are distinguished using image processing techniques. Finally, K Nearest Neighbour (KNN) classifier was used for character recognition. This method has been tested on available data set that has different images of the background, considering distance, and angel of view so that the correct extraction rate of plate reached at 98 recognition rate achieved at 99.12 recognition stage on Persian vehicle data set and we achieved 99 recognition rate.

    07/24/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • Novel and Fast Algorithm for Extracting License Plate Location Based on Edge Analysis

    Nowadays in developing or developed countries, the Intelligent Transportation System (ITS) technology has attracted so much attention to itself. License Plate Recognition (LPR) systems have many applications in ITSs, such as the payment of parking fee, controlling the traffic volume, traffic data collection, etc. This paper presents a new and fast method for license plate extraction based on edge analysis. our proposed method consist of four stage, which are edge detection, non-useable edge and noise removing, edge analysis and morphology-based license plate extraction. In the result part, the proposed algorithm is applied on vehicle database and the accuracy rate reached 98 From the experimental results it is shown that the proposed method gives fairly acceptable level of accuracy for practical license plate recognition system.

    07/24/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • Recognition of Handwritten Persian/Arabic Numerals Based on Robust Feature Set and K-NN Classifier

    This paper has been withdrawn by the author due to a crucial sign error in equation 2 and some mistake in Table 1 information. please let me for changing this information and updating this paper.

    07/24/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • Novel and Automatic Parking Inventory System Based on Pattern Recognition and Directional Chain Code

    The objective of this paper is to design an efficient vehicle license plate recognition System and to implement it for automatic parking inventory system. The system detects the vehicle first and then captures the image of the front view of the vehicle. Vehicle license plate is localized and characters are segmented. For finding the place of plate, a novel and real time method is expressed. A new and robust technique based on directional chain code is used for character recognition. The resulting vehicle number is then compared with the available database of all the vehicles so as to come up with information about the vehicle type and to charge entrance cost accordingly. The system is then allowed to open parking barrier for the vehicle and generate entrance cost receipt. The vehicle information (such as entrance time, date, and cost amount) is also stored in the database to maintain the record. The hardware and software integrated system is implemented and a working prototype model is developed. Under the available database, the average accuracy of locating vehicle license plate obtained 100 training, we tested our scheme on whole samples and obtained 100 recognition rate. Further we tested our character recognition stage on Persian vehicle data set and we achieved 99

    07/23/2014 ∙ by Reza Azad, et al. ∙ 0 share

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  • A robust and adaptable method for face detection based on Color Probabilistic Estimation Technique

    Human face perception is currently an active research area in the computer vision community. Skin detection is one of the most important and primary stages for this purpose. So far, many approaches are proposed to done this case. Near all of these methods have tried to find best match intensity distribution with skin pixels based on popular color spaces such as RGB, HSI or YCBCR. Results show that these methods cannot provide an accurate approach for every kind of skin. In this paper, an approach is proposed to solve this problem using a color probabilistic estimation technique. This approach is including two stages. In the first one, the skin intensity distribution is estimated using some train photos of pure skin, and at the second stage, the skin pixels are detected using Gaussian model and optimal threshold tuning. Then from the skin region facial features have been extracted to get the face from the skin region. In the results section, the proposed approach is applied on FEI database and the accuracy rate reached 99.25 be used for all kinds of skin using train stage which is the main advantage among the other advantages, such as Low noise sensitivity and low computational complexity.

    07/23/2014 ∙ by Reza Azad, et al. ∙ 0 share

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