The Impact of Curviness on Four Different Image Sensor Forms and Structures

Wei, Wen‐Cheng J.; Khatibi, Siamak

doi:10.3390/s18020429

Cited by 4 publications

(6 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The most popular geometric figures are: triangles, squares, and hexagons; these are the only regular shapes that tessellates the plane with no gaps [49]. In studies performed for the purposes of the article hexagonal grid was used-the higher usefulness of the hexagon over other figures has been repeatedly confirmed in the case of spatial analyses [50][51][52], as well as in other cases [53][54][55][56][57]. The aim of this research was to find the optimal size of the hexagonal grid, to the level of which the data can be generalized, without a significant decrease in the reliability of spatial modeling for various sustainable heritage management needs.…”

Section: Methodsmentioning

confidence: 99%

Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling

2019

View full text Add to dashboard Cite

Cultural heritage is a very important element affecting the sustainable development. To analyze the various forms of spatial management inscribed into sustainable development, information on the location of objects and their concentration at specific areas is necessary. The main goal of the article was to show the possibility of using various GIS tools in modeling the distribution of historical objects. For spatial analysis, it is optimal to use the point location of objects. Often, however, it is extremely difficult, laborious, expensive, and sometimes impossible to obtain. Thus, various map content generalizations were analyzed in the article; the main goal was to find the level for which the data with an acceptable loss of accuracy can be generalized. Such analyses can be extremely useful in sustainable heritage management. Article also shows how cultural heritage fits into the sustainable heritage management. The research included non-movable monuments in Poland. The obtained results showed the universality of this type of research both in the thematic sense (can be used for various types of objects) and spatial sense (can be performed locally, at the country level, or even at the continental level).

show abstract

Section: Methodsmentioning

confidence: 99%

Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling

2019

View full text Add to dashboard Cite

show abstract

“…The virtual hexagonal enriched image has a hexagonal pixel form on a hexagonal arrangement. The generation process is similar to the resampling process in [17,18], which has three steps: projecting the original image pixel intensities onto a grid of sub-pixels; estimating the values of subpixels at the resampling positions; estimating each new hexagonal pixel intensity in a new hexagonal arrangement where the subpixels are projected back to a hexagonal grid, which are shown as red grids in Figure 2. In this arrangement the distance between each two hexagonal pixels is the same and the resolution of the generated Hex_E image is the same as the original image.…”

Section: Image Generationmentioning

confidence: 99%

A Common Assessment Space for Different Sensor Structures

Wei

Kajínek

Khatibi

et al. 2019

Sensors

Self Cite

View full text Add to dashboard Cite

The study of the evolution process of our visual system indicates the existence of variational spatial arrangement; from densely hexagonal in the fovea to a sparse circular structure in the peripheral retina. Today’s sensor spatial arrangement is inspired by our visual system. However, we have not come further than rigid rectangular and, on a minor scale, hexagonal sensor arrangements. Even in this situation, there is a need for directly assessing differences between the rectangular and hexagonal sensor arrangements, i.e., without the conversion of one arrangement to another. In this paper, we propose a method to create a common space for addressing any spatial arrangements and assessing the differences among them, e.g., between the rectangular and hexagonal. Such a space is created by implementing a continuous extension of discrete Weyl Group orbit function transform which extends a discrete arrangement to a continuous one. The implementation of the space is demonstrated by comparing two types of generated hexagonal images from each rectangular image with two different methods of the half-pixel shifting method and virtual hexagonal method. In the experiment, a group of ten texture images were generated with variational curviness content using ten different Perlin noise patterns, adding to an initial 2D Gaussian distribution pattern image. Then, the common space was obtained from each of the discrete images to assess the differences between the original rectangular image and its corresponding hexagonal image. The results show that the space facilitates a usage friendly tool to address an arrangement and assess the changes between different spatial arrangements by which, in the experiment, the hexagonal images show richer intensity variation, nonlinear behavior, and larger dynamic range in comparison to the rectangular images.

show abstract

“…In [ 30 ], the gradient is proved to be an effective parameter for examining the impact of different sensor grids and pixel forms on curviness. In this paper, the histogram of gradient (HoG) is used for evaluating the characteristic of the sensors having different configurations.…”

Section: Implementing Histogram Of Gradient In Different Configuramentioning

confidence: 99%

“… The grid and pixel are hexagonal and square respectively and there is no or fixed gap in [ 29 ], where the hexagonal grid is generated by a half-pixel shifting, its results show that the generated hexagonal images are superior in detection of curvature edges to the square images. The grid and pixel are hexagonal and there is no gap [ 30 ]. In this work, the impact of the three sensor properties, the grid structure, pixel form and fill factor, is examined by curviness quantification using gradient computation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Virtual Deformable Image Sensors: Towards to a General Framework for Image Sensors with Flexible Grids and Forms

Wei

Khatibi

2018

Sensors

Self Cite

View full text Add to dashboard Cite

Our vision system has a combination of different sensor arrangements from hexagonal to elliptical ones. Inspired from this variation in type of arrangements we propose a general framework by which it becomes feasible to create virtual deformable sensor arrangements. In the framework for a certain sensor arrangement a configuration of three optional variables are used which includes the structure of arrangement, the pixel form and the gap factor. We show that the histogram of gradient orientations of a certain sensor arrangement has a specific distribution (called ANCHOR) which is obtained by using at least two generated images of the configuration. The results showed that ANCHORs change their patterns by the change of arrangement structure. In this relation pixel size changes have 10-fold more impact on ANCHORs than gap factor changes. A set of 23 images; randomly chosen from a database of 1805 images, are used in the evaluation where each image generates twenty-five different images based on the sensor configuration. The robustness of ANCHORs properties is verified by computing ANCHORs for totally 575 images with different sensor configurations. We believe by using the framework and ANCHOR it becomes feasible to plan a sensor arrangement in the relation to a specific application and its requirements where the sensor arrangement can be planed even as combination of different ANCHORs.

show abstract

The Impact of Curviness on Four Different Image Sensor Forms and Structures

Cited by 4 publications

References 23 publications

Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling

Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling

A Common Assessment Space for Different Sensor Structures

Virtual Deformable Image Sensors: Towards to a General Framework for Image Sensors with Flexible Grids and Forms

Contact Info

Product

Resources

About