A Study on Digital Documentation of Precise Monitoring for Microscale Displacements within the Tomb of King Muryeong and the Royal Tombs in Gongju, Korea

The tomb complex of the royal family from the period of the Ungjin Baekje Kingdom (475 to 538 AD) in Gongju, Korea, contains the tomb of King Muryeong and other royal tombs. After the excavation of the tomb of King Muryeong in 1971, these tombs were opened up to the public, without the establishment of systems for their safety, conservation and management. The tombs have consequently experienced rapid environmental changes and suffered various damages. In this study, specific vulnerable parts inside the tombs were selected for deviation analysis using 3D scanning, and 3D image models were constructed on this basis. Progressive displacement was identified in tomb No. 5, and basic data for future investigations was acquired from tomb No. 6 and the tomb of King Muryeong. In the deviation analysis for the southern plastered wall of tomb No. 5, the damage was not found to exceed the ranges of ±18 mm and ±2 mm. However, the lintel stone was found to be sagging by 0.32 mm on average, and the distance between the walls to have increased by 0.36 mm on average. Direct water seepage occurring in tomb No. 5 is considered to be increasing the damage within the tomb, such as the dropping and sagging of the lintel. The 3D image models constructed in this study will play an important role as baseline data for future research, and can be used to discuss a secure conservation scheme for the tombs through cross-validation with precise measurement monitoring.

High Capacity Reversible Steganography on CMY and HSI Color Images Using Image Interpolation

Steganography using image interpolation has created a new research area in multimedia communication. A reversible data concealing in HSI and CMY color models using image interpolation is proposed in this paper. The HSI and CMY image models are interpolated using High Capacity Reversible Steganography (CRS) technique. The median plane of both HSI and CMY color models are selected for secret message bit concealing. The secret message bits are concealed in the cover plane by Exclusive OR (XOR) operation. Since the cover image is recovered after secret message bit retrieval, this finds application in military and medical imaging applications. The experimental results of proposed scheme showed very high embedding capacity of about 16 bits in each pixel location of calculated pixel value, good image quality with a surface similarity index measure (SSIM) value 1 and high PSNR. Also, high robustness is achieved on comparing with the existing works.

Morphological analysis of mosaic shapes with directed relationships based on attribute and relational model representations

We introduce attribute and relational representations of mosaic image models with directed relationships between regions. Attribute representations of asymmetric relational models based on stacking, ranking and integral descriptions are considered. We propose some morphological shape similarity measures based on relational models. We show that using the same oriented relational model, various morphological operators can be constructed, in particular, of Serra- or Pyt’ev type. Some constructive methods for the design of such morphological operators in an attribute and relational domains are proposed. From this consideration we also extract a new morophlogical scheme for two-stage mutual adaptive image-and-shape joint filtering: at the first step, the shape is simplified (projected) with regard to the image to be projected, and at the second step, the image is simplified (projected) with regard to the simplified (projected) shape.

Capturing and modifying the perceived traits of all possible faces

The diversity in appearance of human faces and their naturalistic viewing conditions give rise to an expansive stimulus space over which humans perceive numerous psychological traits (e.g., perceived trustworthiness). Current scientific models characterize only few of these traits, and over only a tiny fraction of possible faces. Here we show that generative image models from machine learning combined with over 1 million human judgments can capture more than 30 traits over a near-infinite set of face stimuli. This makes it possible to then seamlessly infer and manipulate the psychological traits of arbitrary face photograph inputs and generate infinite synthetic photorealistic face stimuli along those dimensions. The predictive accuracy of our model approaches human inter-rater reliability, which our simulations suggest would not have been possible with previous datasets having fewer faces, fewer trait ratings, or using low-dimensional feature representations.

Persepsi Visual Penyandang Tunagrahita: Studi Deskriptif Olah Gambar Pada Sekolah Luar Biasa Yayasan Amal Mulia

People with tunagrahita are generally categorized as mental retardation. Several studies have seen that one of the effective learning concepts is through visual and audio-visual forms. But in drawing education, mentally retarded persons have different patterns in response to visual meaning. Visual perception is built on coarse motor concepts in processing images which are not always done easily. This research is developed with a descriptive qualitative methodology to see and describe what forms and image models are easy to difficult the draw process. Retrieval of the research data was through mentally retarded children from the Extraordinary School of the Amal Mulia Foundation by processing images in three forms, namely lines, shape models, and combinations of shapes. The preliminary findings in this study were that students with mental retardation had difficulties in drawing shapes that were not straight or solid, such as curves and circles, even though the students were still able to process according to directions in not too long. Keywords: mental retardation; drawing; visual perception; shape models; education.

MORPHOLOGICAL IMAGE ANALYSIS BASED ON ATTRIBUTE AND RELATIONAL REPRESENTATIONS OF MOSAIC IMAGE MODELS

A unified scheme for morphological analysis based on attribute and relational representations of mosaic image models is proposed. We consider 4 main types of model representation: functional-attribute (2D feature map), functional-relational (4D relational map), structure-resource-attribute (an area list with resources and attributes), and structure-resource-relational (a graph, which nodes correspond to regions and edges – to relations and both having resource attributes). In this case, the forms of representation of the model are equivalent to each other, in the sense that they contain the same information, there is a one-to-one correspondence between them, and the formulas for the transition from one representation to another can be written out explicitly. In this scheme, the construction of specific morphological operator for some complete image model presumes the separation of this model into two parts: the guiding (modifying) part, which determines the transformation algorithm, and the guided (modifiable) part to be transformed. These two parts of the model can intersect, therefore cannot be called “variable” and “constant” components. As a basic sample, we consider the halftone Pyt’ev morphology. We explore the specifics of different-sort models, introduce the mutual models and propose different tools for creation of model-based morphological operators. Further, various other morphological systems can be described and explored using the proposed generalized approach.

Web-based Exploration of Annotated Multi-Layered Relightable Image Models

We introduce a novel approach for exploring image-based shape and material models registered with structured descriptive information fused in multi-scale overlays. We represent the objects of interest as a series of registered layers of image-based shape and material data. These layers are represented at different scales and can come out of a variety of pipelines. These layers can include both Reflectance Transformation Imaging representations, and spatially varying normal and Bidirectional Reflectance Distribution Function fields, possibly as a result of fusing multi-spectral data. An overlay image pyramid associates visual annotations to the various scales. The overlay pyramid of each layer is created at data preparation time by either one of the three subsequent methods: (1) by importing it from other pipelines, (2) by creating it with the simple annotation drawing toolkit available within the viewer, and (3) with external image editing tools. This makes it easier for the user to seamlessly draw annotations over the region of interest. At runtime, clients can access an annotated multi-layered dataset by a standard web server. Users can explore these datasets on a variety of devices; they range from small mobile devices to large-scale displays used in museum installations. On all these aforementioned platforms, JavaScript/WebGL2 clients running in browsers are fully capable of performing layer selection, interactive relighting, enhanced visualization, and annotation display. We address the problem of clutter by embedding interactive lenses. This focus-and-context-aware (multiple-layer) exploration tool supports exploration of more than one representation in a single view. That allows mixing and matching of presentation modes and annotation display. The capabilities of our approach are demonstrated on a variety of cultural heritage use-cases. That involves different kinds of annotated surface and material models.