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Hand Detection and Tracking Using Depth and Color Information
Minsun Park, Md. Mehedi Hasan, Jaemyun Kim and Oksam Chae
International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV 2012, USA)
The detection and tracking of a hand is an emerging research issue now-a-days to control the devices by hand motion.... more The detection and tracking of a hand is an emerging research issue now-a-days to control the devices by hand motion. Conventional hand detection methods use color and shape information from a RGB camera. With the recent advent of the depth camera, some researchers show that they can improve the performance of hand detection by combining the color (or intensity) information with the information from the depth camera. In this paper, we propose a novel method for hand detection using both color and depth information from Microsoft’s Kinect device. The proposed method extract the candidate hand regions from the depth image and select the best candidate based on the color and shape feature of each candidate regions. Then the contour of the selected candidate is determined in the higher resolution RGB image to improve the positional accuracy. For the tracking of the detected hand, we propose the boundary tracking method based on Generalized Hough Transform (GHT). The experimental results show that proposed method can improve the accuracy of hand motion detection over conventional methods.
Cloud Architecture for Lossless Image Compression by Efficient Bit-plane Similarity Coding
MAHBUB MURSHED, SM ZAHID ISHRAQUE, MD. MEHEDI HASAN, OKSAM CHAE, Proceeding of the 2012 FTRA International Conference on Advanced IT, Engineering and Management, February 2012.
Cloud computing platform provides enormous opportunity to the users for fast computation, sharing and transmission.... more
Cloud computing platform provides enormous opportunity to the users for fast computation, sharing and transmission. Satellite image, geographical image, and aerial photograph have high resolutions with many different colors. Generally, image compression algorithms reduce data redundancy by encoding spatial dependencies. To bring out spatial dependencies
between these large volumes of data is very difficult and time consuming process. Moreover, the compression of these images has to be lossless to ensure faithful reproduction. Bit-plane coding technique allows us to take advantages from neighborhood similarity, often found in image plane which is more useful than accounting on gray level similarity. Moreover, bit-planes allow parallel processing of each plane in the clouds. In this paper, we present an approach to use the quadtree structures for efficient and progressive image compression using the cloud architecture which shows high compression ratios without any loss. Our proposed algorithm has simple structure and can compress/decompress any image very fast in the clouds while necessary.
Hawkeye: Cloud Computing Based Automated Video Error Detection in Real-time
Md. Mehedi Hasan, Kiok Ahn, Mahbub Murshed, Oksam Chae, INFORMATION Journal (Accepted)
With the rapid development of video surveillance and broadcast systems monitoring the video quality becomes an... more With the rapid development of video surveillance and broadcast systems monitoring the video quality becomes an important aspect to assure better quality of service. Error detection is an important technique to measure the quality of videos transmitted over unreliable network. With the advent of HDTV previously subtle errors in videos are becoming more prominent. In this paper we want to propose a next generation cloud based video error detection system using image/video processing technology for making the detection process real-time. At first, we introduce an automatic video error detection method and then propose a cloud computing platform. Finally we integrate error detection method with cloud computing platform named Hawkeye to achieve a real time video error detection system which ensures contents integrity and minimizes testing time and efforts required to keep ahead of other conventional quality check system. Extensive experiments on prominent datasets and telecasted videos show that the proposed algorithm is very much efficient to detect errors for video broadcast and surveillance applications in terms of computation time and the detection of distorted frames
Statistica Binary edge frequency accumulation model for moving object detection.
Mahbub Murshed, Adin Ramirez, Jaemyun Kim and Oksam Chae, “Statistica Binary edge frequency accumulation model for moving object detection”, Accepted, International Journal of Innovative Computing, Information and Control (ISSN 1349-4198), Volume 8, Number 6, June 2012. [SCIE], Impact Factor 1.664
Moving Object Tracking - An Edge Segment-based Approach
Mahbub Murshed, Md. Hasanul Kabir, Oksam Chae, “Moving Object Tracking - An Edge Segment-based Approach”, International Journal of Innovative Computing, Information and Control (ISSN 1349-4198), Volume 7, Number 7, July 2011. (IJICIC) [SCIE], Impact Factor 2.932
In this paper, an edge segment based tracking algorithm, that is capable of identifying moving objects in image... more
In this paper, an edge segment based tracking algorithm, that is capable of identifying moving objects in image sequence is proposed. Since, segmenting objects from a sequence image is not easy, traditional object tracking algorithms fetches difficulty due to large variation of object shape, orientation, motion and size between frames. One object may consist of several parts with different motion. Additionally, object’s motion and shape is less consistent within frames. To cope with these difficulties, our algorithm makes efficient use of edge-segments based on the Canny edge map by utilizing the edge structure in the moving object region. Curvature-based features are used for moving edge
registration due to its transformation invariance nature. We use the maximum curvature correspondences between two edge segments to define the 2D affine transformation that relates the two segments by solving a linear system. The edge segment registration error is also minimized. A Kalman filter based predictor is used for tracking each individual edge segments. Edge-segments are clustered using a weighted mean shift algorithm. Finally, a group motion tracker is used for tracking moving object from each cluster. Experiments show that our edge-segment based tracking algorithm can track moving objects or part of the object efficiently under varying illumination conditions and partial occlusion.
Moving edge segment matching for the detection of moving object.
Mahbub Murshed, Adin Ramirez, and Oksam Chae. 2011. Moving edge segment matching for the detection of moving object. In Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I (ICIAR'11), Mohamed Kamel and Aurélio Campilho (Eds.), Vol. Part I. Springer-Verlag, Berlin, Heidelberg, 274-283.
We propose a segment based moving edge detection algorithm
by building association from multi-frames of the... more
We propose a segment based moving edge detection algorithm
by building association from multi-frames of the scene. A statistical background model is used to segregate the moving segments that utilize shape and position information. Edge specific knowledge depending upon background environment is computed and thresholds are determined automatically. Statistical background model gives flexibility for matching background edges. Building association within the moving segments of multi-frame enhances the detection procedure by suppressing noisy detection of flickering segments that occurs frequently due to noise, illumination variation and reflectance in the scene. The representation of edge as edge segment allows us to incorporate this knowledge about the background environment. Experiments with noisy images under varying illumination changing situation demonstrates the robustness of the proposed method in comparison with existing edge pixel based moving object detection methods.
Handwritten Signature Verification System using Artificial Intelligence
Mahbub Murshed, S. M. Saifur Rahman, K. M. Hasan Al Noor, Md. Kamrul Islam, “Handwritten Signature Verification System using Artificial Intelligence”, 6th International Conference on Computer and Information Technology, ICCIT2003, December, 2003, Dhaka, Bangladesh.
A Parametric approach to Bangla to English Statistical Machine Translation for Complex Bangla Sentences- Step 1
Mohammad Gias Uddin, Mahbub Murshed, Muhammad Abul Hasan, “A Parametric approach to Bangla to English Statistical Machine Translation for Complex Bangla Sentences- Step 1”, 8th International Conference on Computer and Information Technology, ICCIT2005, December 2005, Dhaka, Bangladesh
Lossless Digital Image Compression using Quad-Tree Gray-Code Embedded Bit Plane Imaging Method
Mohammad Gias Uddin, Mahbub Murshed, Muhammad Abul Hasan,”Lossless Digital Image Compression using Quad-Tree Gray-Code Embedded Bit Plane Imaging Method” 8th International Conference on Computer and Information Technology, ICCIT2005, December 2005, Dhaka, Bangladesh
Off-line Based Statistical Signature Verification of Unconstrained Signatories
Mahbub Murshed, Mohammad Gias Uddin, “Off-line Based Statistical Signature Verification of Unconstrained Signatories”, 8th International Conference on Computer and Information Technology, ICCIT2005, December 2005, Dhaka, Bangladesh
A Quadratic Bit-Plane Block Similarity (QBPS) Approach for Lossless Image Compression
Mahbub Murshed, Md. Hasanul Kabir, Oksam Chae, “A Quadratic Bit-Plane Block Similarity (QBPS) Approach for Lossless Image Compression”, The 2009 International Conference on Image Processing, Computer Vision, and Pattern Recognition, pp. 526-531, July 13-16, 2009, Las Vegas, Nevada, USA
Photographic images such as medical image,
geographical image, satellite image, have many colors and
thus it... more
Photographic images such as medical image,
geographical image, satellite image, have many colors and
thus it becomes much difficult to bring out spatial dependencies.
Additionally, the compression of these images has to
be lossless, to ensure faithful reproduction. Bitplane coding
technique allows us to take advantages from neighborhood
similarity, often found in image plane which is more useful
than accounting on gray level similarity measures. In this
paper, we present an approach to use the quadtree structures
for efficient progressive image compression approach which
shows high compression ratios without any loss. Here the
image is treated as a set of bitplanes. The compressed
version of the image is represented by an encoded linear
byte array. Our proposed algorithm has simple structure and
can compress/decompress any image in less time. The algorithm is extensively compared to different standard lossless
compression methods.
Moving Object Tracking - A parametric edge tracking approach
Mahbub Murshed, M. Ali Akber Dewan†, and Oksam Chae, “Moving Object Tracking - A parametric edge tracking approach”, 12th International Conference on computer and information technology (ICCIT2009), pp. 471-476, December, 2009. Dhaka, Bangladesh.
In this paper, an edge based tracking algorithm is proposed. Our algorithm makes efficient use of edge-segment on the... more In this paper, an edge based tracking algorithm is proposed. Our algorithm makes efficient use of edge-segment on the Canny edge map by utilizing the edge structure in the moving object region. Curvature-based features are used for moving edge registration. We use the maximum curvature correspondences between two edge segments then the 2D affine transformation computes their movement by solving a system of linear equations. The registration error is then minimized. A Kalman Filter is used to track each individual edge segments. Segments are clustered using a k-mean algorithm. Finally, a group motion tracker is used for tracking moving object from each cluster. Experiments show that our edge-segment based tracking algorithm can track moving objects efficiently under varying illumination conditions.
Faster Detection of Independent Lossy Compressed Block Errors in Images and Videos
International Journal of Signal Processing, Image Processing and Pattern Recognition (Accepted).
An effecting compression algorithm removes the redundancy of image signal, when we want to represent high quality... more An effecting compression algorithm removes the redundancy of image signal, when we want to represent high quality videos and images with lower bit rate. Removal of statistical correlation and insignificant components of image signal make the corresponding videos and images highly compressed. This paper represents a new algorithm to measure the blocking artifacts of videos by analyzing the distortions of local properties of image signals like dominant edge magnitude and direction. We also want to incorporate light weighted human vision measurement system like edge information to measure video artifacts in real time. Then simple bucket filling approach is applied, where the particular bucket contains the maximum value also indicating the block boundaries that are passed to the report module. After computing distortion measure a proposed detection approach is used to capture the distorted frames. Extensive experiments on various videos show that the new algorithm is very much efficient and faster to measure the independent lossy compressed block errors in real time video error detection applications.
Fast and Reliable Structure-Oriented Distortion Measure for Video Processing
Md. Mehedi Hasan, Kiok Ahn, JeongHeon Lee, SM Zahid Ishraque, Oksam Chae, " Fast and Reliable Structure-Oriented Distortion Measure for Video Processing", advanced science letters, (accepted), IMPACT FACTOR = 1.253
Structure-Oriented video distortions detection significantly impacts the effectiveness of video processing algorithms.... more Structure-Oriented video distortions detection significantly impacts the effectiveness of video processing algorithms. To transmit high quality videos and images with low bit rate, an effective compression algorithm removes the redundancy of statistical correlation and insignificant component of image signal. In video broadcasting and surveillance systems, not only the compression based but also content based distortion occurs during its transmission through wired or over wireless channel. To overcome these issues we first propose a measurement of these artifacts of videos by analyzing the distribution of local properties of image signals like dominant edge magnitude and direction to assure better Quality of Service. We also propose a metric to detect damaged frame by considering the contextual information, such as their consistency and edge continuity. According to the statistical information the distorted frames are then estimated based on the characteristics of their surrounding frames. Extensive experiments on prominent datasets and telecasted videos show that the proposed algorithm is very much efficient to detect errors for video broadcast and surveillance applications in terms of computation time and the detection of distorted frames.
Hawkeye: Real-time Video Error Detection Using Cloud Computing Platform
MD. MEHEDI HASAN, KIOK AHN, SM ZAHID ISHRAQUE, OKSAM CHAE, Proceeding of the 2012 FTRA International Conference on Advanced IT, Engineering and Management, February 2012.
Cloud computing is an emerging model of business computing that delivers computing as a service rather than a product,... more Cloud computing is an emerging model of business computing that delivers computing as a service rather than a product, whereby shared resources, software and information are provided to computers and other devices as a utility over network. In recent years cloud computing has been put forward. It connects millions of computers to a super cloud. With the advent of HDTV previously subtle errors in videos are becoming more prominent, previously an extensive research field. In this paper we want to propose a next generation cloud based video error detection system using image/video processing technology. Hawkeye is an automatic error detection system which ensures contents integrity and minimizes testing time and efforts required to keep ahead of other conventional quality check system.
Measuring Blockiness of Videos using Edge Enhancement Filtering
Md. Mehedi Hasan, Kiok Ahn, Oksam Chae, ”Measuring Blockiness of Videos using Edge Enhancement Filtering”, International Conference on Signal Processing, Image Processing and Pattern Recognition, CCIS 260, pp. 10-19, 2011.
To represent high quality videos or images with low bit rate, an effective compression algorithm removes the... more To represent high quality videos or images with low bit rate, an effective compression algorithm removes the redundancy because of statistical correlation and also the insignificant component of image signal. This paper represents a new algorithm to measure the blocking artifacts of videos by analyzing the distortions of local properties of image signals like dominant edge magnitude and direction. Extensive experiments on various videos show that the new algorithm is very much efficient and faster to measure the blocking artifacts in real time video error detection applications.
Blocking Artifact Detection by Analyzing the Distortions of Local Properties in Images
Md. Mehedi Hasan, Kiok Ahn, Md. Shariful Haque, Oksam Chae , “Blocking Artifact Detection by Analyzing the Distortions of Local Properties in Images”, International Conference on Computer and Information Technology, accepted, (22-24)December 2011.
Now-a-days, recent trend is to represent high quality images or videos by using less bit representation. To represent... more Now-a-days, recent trend is to represent high quality images or videos by using less bit representation. To represent high quality videos or images with low bit rate, an effective compression algorithm removes the redundancy because of statistical correlation and also the insignificant component of image signal. This paper represents a new algorithm to measure the blocking artifacts of videos by analyzing the distortions of local properties of image signals like dominant edge magnitude and direction. For this purpose sobel convolution mask is used rather than kirsch mask to make the detection process faster and to model video noises that occur in broadcasting systems. Extensive experiments on various videos show that the new algorithm is very much efficient to measure the blocking artifacts in real time video error detection applications.
Object Detection through Edge Behavior Modeling
Published in AVSS 2011
The detection of moving objects depends on the accuracy of the model used to represent the background. Common... more The detection of moving objects depends on the accuracy of the model used to represent the background. Common pixel-based and naive edge-based approaches have many drawbacks in dynamic environments, e.g., false detections with noise. We propose a novel background model that encodes the background as edges, building a statistical distribution per segment that represents the edge behavior. We build the background distributions using a kernel-based approach; the moving objects are detected as the edges that deviate from the distributions. The method does adaptive thresholding to the edges, which maintains their shape and boosts the detection accuracy. Sets of gradient distributions are incorporated into the model, to determine edges that lie within the distributions, but are moving edges. The number of distributions is handled dynamically, allowing them to increase and decrease accordingly to the situation. The experiments show that the proposed method improves the detection rates, due to its robustness against illumination changes.