A Fast Processing Algorithm for Lidar Data Compression Using Second Generation Wavelets

B. Pradhan,K. Sandeep,Shattri Mansor,Abdul Rahman Ramli,Abdul Rashid B. Mohamed Sharif 大韓遠隔探査學會 2006 大韓遠隔探査學會誌 Vol.22 No.1

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the LIDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to `modify` the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original LIDAR data. The results show that this method can be used for significant reduction of data set.

A Fast Processing Algorithm for Lidar Data Compression Using Second Generation Wavelets

Pradhan B.,Sandeep K.,Mansor Shattri,Ramli Abdul Rahman,Mohamed Sharif Abdul Rashid B. The Korean Society of Remote Sensing 2006 大韓遠隔探査學會誌 Vol.22 No.1

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

Rockfall Source Identification Using a Hybrid Gaussian Mixture-Ensemble Machine Learning Model and LiDAR Data

Fanos, Ali Mutar,Pradhan, Biswajeet,Mansor, Shattri,Yusoff, Zainuddin Md,Abdullah, Ahmad Fikri bin,Jung, Hyung-Sup The Korean Society of Remote Sensing 2019 大韓遠隔探査學會誌 Vol.35 No.1

The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

Rockfall Source Identification Using a Hybrid Gaussian Mixture-Ensemble Machine Learning Model and LiDAR Data

Ali Mutar Fanos,Biswajeet Pradhan,Shattri Mansor,Zainuddin Md Yusoff,Ahmad Fikri bin Abdullah,정형섭 대한원격탐사학회 2019 大韓遠隔探査學會誌 Vol.35 No.1

The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms (ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

Interoperability for Smart Home Environment Using Web Services

Thinagaran Perumal,Abdul Rahman Ramli,Chui Yew Leong,Shattri Mansor,Khairulmizam Samsudin 보안공학연구지원센터 2008 International Journal of Smart Home Vol.2 No.4

Recent advances in computing and communication technologies paved the growth for applications and devices in smart home environment. A typical smart home is highly characterized by heterogeneity elements that need to perform joint execution of tasks in an efficient manner. Although there are huge growth of services, applications and devices in smart home environment, the interoperability elements still seems ambiguous. Being a distributed architecture, smart home environment needs certain degree of interoperability to manage sub-systems comprising of different platforms. Generally, these sub-systems are developed in isolation and consist of different operating system and tier of services. There is need for a cross-platform interoperability that could make the sub-systems ‘talk’ each other and operate in an interoperable fashion within smart home environment. Web Services seems to be the emerging technology that could lead the way in providing greater interoperability. In this paper we describe the potential of Web Services technology using Simple Object Access Protocol (SOAP) in addressing the interoperability requirements for smart home environment. The SOAP protocol provides data exchange mechanism as well as optimized performance for interoperation among sub-systems residing in smart home environment. The proposed system performance is evaluated to demonstrate a complete, bi-directional real-time management of sub-systems in smart home environment.