Local Color Voxel and Spatial Pattern for 3D Textured Recognition

3D textured retrieval including shape, color dan pattern is still a challenging research. Some approaches are proposed, but voxel-based approach has not much been made yet, where by using this approach, it still keeps both geometry and texture information. It also maps all 3D models into the same dimension. Based on this fact, a novel voxel pattern based is proposed by considering local pattern on a voxel called local color voxel pattern (LCVP). Voxels textured is observed by considering voxel to its neighbors. LCVP is computed around each voxel to its neighbors. LCVP value will indicate uniq pattern on each 3D models. LCVP also quantizes color on each voxel to generate a specific pattern. Shift and reflection circular also will be done. In an additional way, inspired by promising recent results from image processing, this paper also implement spatial pattern which utilizing Weber, Oriented Gradient to extract global spatial descriptor. Finally, a combination of local spectra and spatial and established global features approach called multi Fourier descriptor are proposed. For optimal retrieval, the rank combination is performed between local and global approaches. Experiments were performed by using dataset SHREC'13 and SHREC'14 and showed that the proposed method could outperform some performances to state-of-the-art

Multi Voxel Descriptor for 3D Texture Retrieval

In this paper, we present a new feature descriptors  which exploit voxels for 3D textured retrieval system when models vary either by geometric shape or texture or both. First, we perform pose normalisation to modify arbitrary 3D models  in order to have same orientation. We then map the structure of 3D models into voxels. This purposes to make all the 3D models have the same dimensions. Through this voxels, we can capture information from a number of ways.  First, we build biner voxel histogram and color voxel histogram.  Second, we compute distance from centre voxel into other voxels and generate histogram. Then we also compute fourier transform in spectral space.  For capturing texture feature, we apply voxel tetra pattern. Finally, we merge all features by linear combination. For experiment, we use standard evaluation measures such as Nearest Neighbor (NN), First Tier (FT), Second Tier (ST), Average Dynamic Recall (ADR). Dataset in SHREC 2014  and its evaluation program is used to verify the proposed method. Experiment result show that the proposed method  is more accurate when compared with some methods of state-of-the-art

APLIKASI TATA KELOLA DAN AUDIT SISTEM INFORMASI MENGGUNAKAN FRAMEWORK COBIT

Information technology (IT) has evolved into a technology that is very helpful and even determine the level of performance of an organization. With the help of IT, work processes or business processes that occur in the organization can be done quickly and efficiently. This research attempts to provide an assessment of an IT governance model for EEPIS-ITS with reference to the standard COBIT (Control Objectives for Information and Related Technology). COBIT is an IT Governance standard model that has gained widespread recognition. COBIT standard is used because it has a pretty good compromise in management scope and its detail processes compared to other standards. This study focused on two main domains of COBIT, the Plan and Organize (PO) and Acquire and implement (AI). Methodology of research carried out by literature study and identification of IT management EEPIS-ITS, a form of identification management awareness of the functions of its IT assets in support of the achievement of the vision and mission of the organization, and analysis of current conditions of governance, which is obtained through questionnaires. From both these data, we can see the target maturity (expected maturity level) that is suitable for EEPIS-ITS. IT Management which accompanied the planning and establishment of clear measures from the beginning as it is formed by using the COBIT standard will ensure an effective and efficient management, and making IT assets owned by the primary support of the vision and mission of EEPIS-ITS has been determined

Multi Voxel Descriptor for 3D Texture Retrieval

In this paper, we present a new feature descriptors  which exploit voxels for 3D textured retrieval system when models vary either by geometric shape or texture or both. First, we perform pose normalisation to modify arbitrary 3D models  in order to have same orientation. We then map the structure of 3D models into voxels. This purposes to make all the 3D models have the same dimensions. Through this voxels, we can capture information from a number of ways.  First, we build biner voxel histogram and color voxel histogram.  Second, we compute distance from centre voxel into other voxels and generate histogram. Then we also compute fourier transform in spectral space.  For capturing texture feature, we apply voxel tetra pattern. Finally, we merge all features by linear combination. For experiment, we use standard evaluation measures such as Nearest Neighbor (NN), First Tier (FT), Second Tier (ST), Average Dynamic Recall (ADR). Dataset in SHREC 2014  and its evaluation program is used to verify the proposed method. Experiment result show that the proposed method  is more accurate when compared with some methods of state-of-the-art