A novel color image fusion QoS measure for multi-sensor night vision applications
- Authors: Anwaar, Ul-Haq , Gondal, Iqbal , Murshed, Manzur
- Date: 2010
- Type: Text , Conference proceedings
- Full Text: false
- Description: Color image fusion of visible and infra-red imagery can play an important role in multi-sensor night vision systems that are an integral part of modern warfare. Image fusion minimizes the amount of required bandwidth by transmitting the fused image rather than multiple sensor images. Color image fusion can be achieved by combining inputs from original colored sensors or by employing pseudo colorization and color transfer to grayscale images. Various quality measures have been proposed for multi-sensor grayscale image fusion techniques; but no appropriate quality measure has been devised for the quality evaluation of multi-sensor color image fusion. In this paper, we propose a novel color image fusion quality measure, Color Fusion Objective Index (CFOI) based on colorfulness, gradient similarity and mutual information techniques. Experimental results show the effectiveness of CFOI to evaluate the color and salient feature extraction introduced by color fusion techniques into the final fused imagery as well as its consistency with subjective evaluation.
Automated multi-sensor color video fusion for nighttime video surveillance
- Authors: Ul-Haq, Anwaar , Gondal, Iqbal , Murshed, Manzur
- Date: 2010
- Type: Text , Conference proceedings
- Full Text: false
- Description: In this paper, we present an automated color transfer based video fusion method to attain real-time color night vision capability for night-time video surveillance. We utilize simple RGB Color transfer technique to fused pseudo colored video frames without conversion to any uncorrelated color space. We investigated that final color fusion results greatly depend on the selection of target color Image. Therefore, rather than using any arbitrary target color image based on mere general visual anticipation, we have automated target color image selection using structural similarity and color saturation. We further apply color enhancement to improve final appearance of color fused images. Subjective and objective quality evaluations greatly indicate the effectiveness of our color video fusion method for nighttime video surveillance applications.
VSAMS : Video stabilization approach for multiple sensors
- Authors: Ul-Haq, Anwaar , Gondal, Iqbal , Murshed, Manzur
- Date: 2010
- Type: Text , Conference proceedings
- Relation: 2010 International Conference on Digital Image Computing: Techniques and Applications, Dec. 2010, pp.411-416
- Full Text: false
- Description: Video Stabilization is now considered an old problem which is almost solved but there are still some connecting problems which needs research attention. One of such issues arises due to multiple unstable videos streams coming from multiple sensors which often contain complementary information. To enhance system performance, instability should be removed in a single go rather than stabilizing each sensor individually. This paper proposes a cooperative video stabilization framework, VSAMS for multisensory aerial data based on robust boosting curves which encapsulate stability of high spatial frequency information as used by flying parakeets (budgerigars). For reducing shake and jitter and preservation of actual camera path, a multistage smoothing approach is visualized. Experiments are performed on multisensory UAV data which contains infrared and electro-optical video streams. Subjective and objective quality evaluation proves effectiveness of the proposed cooperative stabilization framework.
A Novel multichannel cognitive radio network with throughput analysis at saturation load
- Authors: Hasan, Rashidul , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: 10th IEEE International Symposium on Network Computing and Applications (NCA), 25-27th August, 2011 Cambridge, MA, p. 1-6
- Full Text: false
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- Description: Opportunistic access of licensed spectrum using a cognitive radio network (CRN) is getting research attraction due to its ability to improve utilisation of this scarce resource without affecting the primary users (PUs). To improve wide acceptability of CRN, it must be equipped with efficient protocols to deal with multiple primary networks to provision QoS guarantee for demand-driven applications by the secondary users (SUs). In this paper, a novel CSMA/CA-based multichannel cognitive radio medium access control (MCR-MAC) protocol is developed by modifying the 4-way handshaking based IEEE 802.11 DCF to dynamically assign contending SUs to free channels using an innovative random arbitration scheme. The paper also presents a detailed analytical model for cognitive interference to the PUs and SUs. The proposed protocol is designed to keep the interference level in check to remain transparent to the PUs. A throughput analysis at saturation load reveals that this fully ad-hoc MCR-MAC is capable of achieving throughput comparable to the ideal scenario (when SUs are equally divided to the channels) without using any centralised infrastructure or dedicated control channel. Extensive simulation results validate the accuracy of the theoretical analysis and establish MCR-MAC as a highly practical solution to construct a CRN in a region overlapped with multiple primary networks to offer data-rate sensitive applications by the SUs.
Action recognition using spatio-temporal distance classifier correlation filter
- Authors: Anwaar-Ul Haq , Gondal, Iqbal , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: 2011 International Conference on Digital Image Computing Techniques and Applications (DICTA), Noosa, QLD, 6th-8th Dec, 2011
- Full Text: false
- Reviewed:
- Description: The problem of recognizing human actions is characterized by complex dynamics and strong variations in their executions. Despite this inconvenience, space-time correlations provide valuable clues for their discrimination. Therefore, space-time correlators like emph{Maximum Average Correlation Height} (MACH) filters have successfully been used for action recognition with encouraging results. However, their utility is challenged due to number of factors: (i) these filters are trained only for one class at a time and separate filters are required for each class increasing computational overhead, (ii) these filters simply take average of similar action instances and behave no better than average filters and (iii) misaligned action datasets create problems for these filters as they are not shift-invariant. In this paper, we address these issues by posing action recognition as a multi-class discrimination problem and propose a emph{single} 3D frequency domain filter, named Action ST-DCCF for multiple action classes that mitigates inherent discrepancies of correlation filters. It presents a different interpretation of correlation filters as a method of applying spatio-temporal transformation to the data rather than simply minimizing correlation energy across all possible shifts. Experiments on a variety of action datasets are performed to evaluate our approach. Experimental results are comparable to the existing action recognition approaches.
- Description: The problem of recognizing human actions is characterized by complex dynamics and strong variations in their executions. Despite this inconvenience, space-time correlations provide valuable clues for their discrimination. Therefore, space-time correlators like \emph{Maximum Average Correlation Height} (MACH) filters have successfully been used for action recognition with encouraging results. However, their utility is challenged due to number of factors: (i) these filters are trained only for one class at a time and separate filters are required for each class increasing computational overhead, (ii) these filters simply take average of similar action instances and behave no better than average filters and (iii) misaligned action datasets create problems for these filters as they are not shift-invariant. In this paper, we address these issues by posing action recognition as a multi-class discrimination problem and propose a \emph{single} 3D frequency domain filter, named Action ST-DCCF for multiple action classes that mitigates inherent discrepancies of correlation filters. It presents a different interpretation of correlation filters as a method of applying spatio-temporal transformation to the data rather than simply minimizing correlation energy across all possible shifts. Experiments on a variety of action datasets are performed to evaluate our approach. Experimental results are comparable to the existing action recognition approaches.
An enhanced-MDP based vertical handoff algorithm for QoS support over heterogeneous wireless networks
- Authors: Sharna, Shusmita , Amin, Mohammad , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: Proceedings of 2011 IEEE International Symposium on Network Computing and Applications (NCA 2011),Cambridge, MA, 25-27th Aug, 2011
- Full Text: false
- Reviewed:
- Description: Vertical handoff plays an important role in guaranteeing users to be always connected in an overlapped multi-network environment. During the vertical handoff procedure, handoff decision is the most important step that affects the normal working of communication. An incorrect handoff decision or selection of a non-optimal network may result in undesirable effects such as higher costs, poor quality of service (QoS) experience, and even dropped communication. Among the existing vertical handoff decision algorithms, the Markov Decision Process (MDP) based algorithm by Stevens-Navarro et al. is promising due to its ability to achieve the optimal expected reward. However, the reward function used by this algorithm is flawed as it favors reducing expected number of vertical handoffs at the expense of diminished expected values of other QoS parameters. This paper presents an extended MDP based algorithm (EMDP) with novel reward function formulation. Analysis shows that EMDP outperforms the MDP based algorithm in terms of improved expected values of all QoS parameters considered while keeping the vertical handoff number reasonably low.
Performance improvement of vertical handoff algorithms for QoS support over heterogenuous wireless networks
- Authors: Sharna, Shusmita , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: Proceedings of the Thirty-Fourth Australasian Computer Science (ASSC 2011), 17th -20th January, Perth, 2011 p. 17-24
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- Reviewed:
- Description: During the vertical handoff procedure, handoff decision is the most important step that affects the normal working of communication. An incorrect handoff decision or selection of a non-optimal network can result in undesirable effects such as higher costs, poor service experience, degrade the quality of service and even break off current communication. The objective of this paper is to determine the conditions under which vertical handoff should be performed in heterogeneous wireless networks. In this paper, we present a comprehensive analysis of different vertical handoff decision algorithms. To evaluate tradeoffs between their performance and efficiency, we propose two improved vertical handoff decision algorithm based on Markov Decision Process which are referred to as MDP_SAW and MDP_TOPSIS. The proposed mechanism assists the terminal in selecting the top candidate network and offer better available bandwidth so that user satisfaction is effectively maximized. In addition, our proposed method avoids unbeneficial handoffs in the wireless overlay networks.
Provisioning delay sensitive service in cognitive radio networks with multiple radio interfaces
- Authors: Hasan, Rashidul , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: Proceedings of the 2011 IEEEE Wireless Communications and Networking Conference (WCNC 2011), 28th-31st March, 2011, New York p 162-167
- Full Text: false
- Reviewed:
- Description: Cognitive radio network (CRN) users are inherently expected to experience widely-varied delays due to the uncertainty in wireless channel availability. Supporting delay sensitive real-time services through CRNs, so that visitors are allowed to experience full-scale networking services by opportunistically sharing the spectrum from a number of existing networks without impacting on the primary users, thus remains a challenging task. This paper presents a novel technique to provision QoS guarantee for delay-sensitive services in CRNs having secondary users equipped with multiple radio interfaces. The technique relies on modeling spectrums holes from multiple primary networks through a resultant channel to enable implementing a single server queuing model with random service interruption. Simulation results using ns-2.33 show that using multiple radio interfaces has sheer strength to reduce CRN delay with fewer number of primary channel sensing.
Abnormal event detection in unseen scenarios
- Authors: Haque, Mahfuzul , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), Melbourne, 9-13th July, 2012. pg 1-6
- Full Text: false
- Reviewed:
- Description: Event detection in unseen scenarios is a challenging problem due to high variability of scene type, viewing direction, nature of scene entities, and environmental conditions. Existing event detection approaches mostly rely on context-specific tuning and training. Consequently, these techniques fail to achieve high scalability in a large surveillance network with hundreds of video feeds where scenario specific tuning/training is impossible. In this paper, we present a generic event detection approach where the extracted low-level features represent the global characteristics of the target scene instead of any context-specific information. From the temporal evolution of these context-invariant features over a timeframe, a fixed number of temporal features are extracted based on the periodicity of significant transition points and associated temporal orders. Finally, top-ranked temporal features are used to train binary classifier-based event models. In this approach, supervised training and exhaustive feature extraction are required only once while building the target event models. During real-time operation in unseen scenarios, event detection is performed based on the trained event models by extracting the required features only. The proposed event detection approach has been demonstrated for abnormal event detection in completely unseen public place scenarios from benchmark datasets without additional training and tuning. Furthermore, the proposed event detection approach has also outperformed recent optical flow based event detection technique.
Analysis of location privacy risk in a plain-text communication based participatory sensing system using subset coding and mix network
- Authors: Sabrina, Tishna , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Full Text: false
Background subtraction for real-time video analytics based on multi-hypothesis mixture-of-Gaussians
- Authors: Haque, Mahfuzul , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 18th-21st Sept, 2012. p1-6
- Full Text: false
- Reviewed:
- Description: Robust background subtraction (BS) is essential for high quality foreground detection in most video analytics systems. Recent BS techniques achieve superior detection quality mostly by exploiting the complementary strengths of multiple background models or processing stages. Consequently, these techniques fail to meet the operational requirements of real-time video analytics due to high computational overhead where BS is just the primary processing task. In this paper, we propose a new BS technique, named multi-hypothesis mixture-of-Gaussians (MH-MOG), suitable for real-time video analytics. The essential idea is to maintain a single background model based on perception-aware mixture-of-Gaussians and then, generating multiple detection hypotheses with different processing bases. Finally, only during the detection stage, the complementary strengths of the hypotheses are exploited to achieve superior detection quality without significant computational overhead. Comprehensive experimental evaluation validates the efficacy of MH-MOG.
Impact on vertical handoff decision algorithm by the network call admission control policy in heterogeneous wireless networks
- Authors: Sharna, Shusmita , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications, Sydney, Sept. 9th-12th 2012, pp.893-898
- Full Text: false
- Reviewed:
- Description: Vertical handoff plays an important role to provide seamless connectivity for a mobile user in an overlapped multinetwork environment. On the other hand in order to maintain network stability, efficient management of available radio resource becomes crucial as network operators want high network utilization and maximum profit generation. For vertical handoff management, existing research works considered these user centric vertical handoff decision algorithm and network centric call admission control as two isolated decision mechanisms in heterogeneous wireless environment. In this paper, however, we propose a correlation between vertical handoff decisions and call admission control policies. We have developed a novel vertical handoff decision model using the Markov decision process based vertical handoff decision algorithm by refining the optimality criterion to factor in the probabilistic consequence of the call dropping rates so that mobile-centric vertical handoff decision algorithm and network-centric call admission control can work through a feedback mechanism to maximize respective objectives in synergy.
Range-free passive localization using static and mobile sensors
- Authors: Iqbal, Anindya , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), San Francisco, CA, 25th-28th June, 2012 p. 1-6
- Full Text: false
- Reviewed:
- Description: In passive localization, sensors try to locate an event without any knowledge of event's emitted power. So, this is a more challenging problem compared to active localization. Existing passive localization schemes use expensive and noise-vulnerable range-based techniques. In this paper, we propose, to the best of our knowledge for the first time, a cost-effective range-free passive localization scheme exploiting hybrid sensor network model where mobile sensors are deployed on demand once an event is sensed by a static sensor. Efficient use of mobile sensors leads to two concomitant optimization problems: (1) positioning the mobile sensors so that the expected possible event location area is minimized; and (2) minimizing their overall traversed distance. To solve the first problem, we have developed a novel arc-coding based range-free localization technique that can accurately define the area of possible event location from the feedback of arbitrarily placed sensors without relying on expensive hardware to estimate range of signals. We have achieved significantly high localization accuracy with a low number of mobile sensors even after considering significant environmental noise. To solve the second problem, three alternative deployment strategies for the mobile sensors were simulated to recommend the best.
Robust background subtraction based on perceptual mixture-of-Gaussians with dynamic adaptation speed
- Authors: Haque, Mahfuzul , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 9th-13th July, Melbourne, 2012
- Full Text: false
- Reviewed:
- Description: In this paper, we propose a new background subtraction technique based on perceptual mixture-of-Gaussians (PMOG). Unlike numerous variants of the classical MOG based approach [1], which can ensure reliable detection result only in known operating environments through proper parameter tuning, PMOG shows superior detection performance across dynamic unconstrained scenarios without any tuning. This is due to PMOG's intrinsic capability of exploiting several perceptual characteristics of human visual system for better understanding of the operating environment to avoid blind reliance on statistical observations. Furthermore, the proposed technique dynamically varies the model adaptation speed, i.e., learning rate, based on observed scene statistics for faster adaptation of changed background and better persistency of detected foreground entities. Comprehensive experimental evaluation on a number of standard datasets validates the robustness of the technique compared to the state-of-the-art.
Unsaturated throughput analysis of a novel interference-constrained multi-channel random access protocol for cognitive radio networks
- Authors: Hasan, Rashidul , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: Proceedings of the 23rd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2012) Sydney 9-12th September, 2012 p. 178-194
- Full Text: false
- Reviewed:
- Description: Opportunistic access of licensed spectrum using a cognitive radio network (CRN) is getting research attraction due to its ability to improve utilisation of this scarce resource without affecting the primary users (PUs). To improve wide acceptability of CRN, it must be equipped with efficient protocols to deal with multiple primary networks to provision QoS guarantee for demand-driven applications by the secondary users (SUs). In this paper, an accurate unsaturated throughput analysis is presented for our novel CSMA/CA-based multi-channel cognitive radio medium access control (MCR-MAC) protocol. Developed by modifying the 4-way handshaking-based IEEE 802.11 DCF, MCR-MAC dynamically assigns contending SUs to free channels using an innovative random arbitration scheme while keeping cognitive interference to the PUs in check by attenuating the packet size. Not only has the analytical model covered the full spectrum, from very light load to saturation, extensive simulation results have validated the accuracy of the analysis.
Undecoded coefficients recovery in distributed video coding by exploiting spatio-temporal correlation: a linear programming approach
- Authors: Ali, Mortuza , Murshed, Manzur
- Date: 2013
- Type: Text , Conference proceedings
- Relation: Proceedings of IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA 2013), Hobart, November 26-28th, 2013, p 1-7
- Full Text: false
- Reviewed:
- Description: Distributed video coding (DVC) aims at achieving low-complexity encoding in contrast to the existing video coding standards' high complexity encoding. According to the Wyner-Ziv theorem this can be achieved, under certain conditions, by independent encoding of the frames while resorting to joint decoding. However, the performance of a Wyner-Ziv coding scheme significantly depends on its knowledge about the spatio-temporal correlation of the video. Unfortunately, correlation statistics in a video widely varies both along the spatial and temporal directions. Therefore, we argue that in a feedback free transform domain DVC scheme the decoder will fail to recover all the transform coefficients with a nonzero probability. Thus, we suggest to integrate a recovery method with the decoder that aims at recovering the undecoded coefficients by exploiting the spatio-temporal correlation of the video. Besides, we extend and modify a recovery scheme, recently proposed in the context of images, for DVC so that it exploits both spatial and temporal correlations in recovering the undecoded coefficients. The essential idea of this scheme is to formulate the recovery problem as a linear optimization problem which can be solved efficiently using linear programming. Our simulation results demonstrated that the proposed scheme can significantly improve the PSNR and visual quality of the erroneous video frames produced by a DVC decoder.
Verifiable and privacy preserving electronic voting with untrusted machines
- Authors: Murshed, Manzur , Sabrina, Tishna , Iqbal, Anindya , Ali, Mortuza
- Date: 2013
- Type: Text , Conference proceedings
- Relation: Proceedings of the 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2013) Melbourne, Vic, 16-18th July, 2013 p. 798-804
- Full Text: false
- Reviewed:
- Description: Designing a trustworthy voting system that uses electronic voting machines (EVMs) for efficiency and accuracy is a challenging task. It is difficult, if not impossible, to ensure the trustworthiness of EVMs that possess computation, storage, and communication capabilities. Thus an electronic voting system that does not assume trusted EVMs is clearly desirable. In this paper, we have proposed a k-anonymized electronic voting scheme that achieves this goal by assuming a hardware-controlled trusted random number generator external to the EVM. The proposed scheme relies on a k-anonymization technique to protect privacy and resort to joint de-anonymization of the votes for counting. Since the joint de-anonymization takes into account all the votes, it is difficult to manipulate an individual vote, even by the EVM, without being detected. Besides the anonymization technique, the proposed scheme relies on standard cryptographic hashing and the concept of floating receipt to provide end-to-end verifiability that prevents coercion or vote trading.
An efficient video coding technique using a novel non-parametric background model
- Authors: Chakraborty, Subrata , Paul, Manoranjan , Murshed, Manzur , Ali, Mortuza
- Date: 2014
- Type: Text , Conference proceedings
- Relation: 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014; Chengdu; China; 14th-18th July 2014 p. 1-6
- Full Text:
- Reviewed:
- Description: Video coding technique with a background frame, extracted from mixture of Gaussian (MoG) based background modeling, provides better rate distortion performance by exploiting coding efficiency in uncovered background areas compared to the latest video coding standard. However, it suffers from high computation time, low coding efficiency for dynamic videos, and prior knowledge requirement of video content. In this paper, we present a novel adaptive weighted non-parametric (WNP) background modeling technique and successfully embed it into HEVC video coding standard. Being non-parametric (NP), the proposed technique naturally exhibits superior performance in dynamic background scenarios compared to MoG-based technique without a priori knowledge of video data distribution. In addition, the WNP technique significantly reduces noise-related drawbacks of existing NP techniques to provide better quality video coding with much lower computation time as demonstrated through extensive comparative studies against NP, MoG and HEVC techniques.
Efficient coding of depth map by exploiting temporal correlation
- Authors: Shahriyar, Shampa , Murshed, Manzur , Ali, Mortuza , Paul, Manoranjan
- Date: 2014
- Type: Text , Conference proceedings
- Relation: 2014 International Conference on Digital Image Computing : Techniques and Applications (DICTA); Wollongong, Australia; 25th-27th November 2014
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text: false
- Description: With the growing demands for 3D and multi-view video content, efficient depth data coding becomes a vital issue in image and video coding area. In this paper, we propose a simple depth coding scheme using multiple prediction modes exploiting temporal correlation of depth map. Current depth coding techniques mostly depend on intra-coding mode that cannot get the advantage of temporal redundancy in the depth maps and higher spatial redundancy in inter-predicted depth residuals. Depth maps are characterized by smooth regions with sharp edges that play an important role in the view synthesis process. As depth maps are more sensitive to coding errors, use of transformation or approximation of edges by explicit edge modelling has impact on view synthesis quality. Moreover, lossy compression of depth map brings additional geometrical distortion to synthetic view. In this paper, we have demonstrated that encoding inter-coded depth block residuals with quantization at pixel domain is more efficient than the intra-coding techniques relying on explicit edge preservation. On standard 3D video sequences, the proposed depth coding has achieved superior image quality of synthesized views against the new 3D-HEVC standard for depth map bit-rate 0.25 bpp or higher.
Efficient HEVC scheme using motion type categorization
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2014
- Type: Text , Conference proceedings
- Relation: 10th International Conference on emerging Networking EXperiments and Technologies (CoNEXT); Sydney, Australia; 2nd-5th December 2014; published in Proceedings of the 2014 Workshop on Design, Quality and Deployment of Adaptive Video Streaming p. 41-42
- Relation: http://purl.org/au-research/grants/arc/DP130103670
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- Reviewed:
- Description: High Efficiency Video Coding (HEVC) standard introduces a number of innovative tools which can reduce approximately 50% bit-rate compared to its predecessor H.264/AVC at the same perceptual video quality whereas the computational time has increased multiple times. To reduce the encoding time while preserving the expected video quality has become a real challenge today for video transmission and streaming especially using low-powered devices. Motion estimation (ME) and motion compensation (MC) using variable-size blocks (i.e., intermodes) require 60-80% of total computational time. In this paper we propose a new efficient intermode selection technique based on phase correlation and incorporate into HEVC framework to predict ME and MC modes and perform faster intermode selection based on three dissimilar motion types in different videos. Instead of exploring all the modes exhaustively we select a subset of modes using motion type and the final mode is selected based on the Lagrangian cost function. The experimental results show that compared to HEVC the average computational time can be downscaled by 34% while providing the similar rate-distortion (RD) performance.