Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The impact of curviness on four different image sensor forms and structures
Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.ORCID iD: 0000-0003-3887-5972
Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.ORCID iD: 0000-0003-4327-117x
2018 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 2, article id 429Article in journal (Refereed) Published
Abstract [en]

The arrangement and form of the image sensor have a fundamental effect on any further image processing operation and image visualization. In this paper, we present a software-based method to change the arrangement and form of pixel sensors that generate hexagonal pixel forms on a hexagonal grid. We evaluate four different image sensor forms and structures, including the proposed method. A set of 23 pairs of images; randomly chosen, from a database of 280 pairs of images are used in the evaluation. Each pair of images have the same semantic meaning and general appearance, the major difference between them being the sharp transitions in their contours. The curviness variation is estimated by effect of the first and second order gradient operations, Hessian matrix and critical points detection on the generated images; having different grid structures, different pixel forms and virtual increased of fill factor as three major properties of sensor characteristics. The results show that the grid structure and pixel form are the first and second most important properties. Several dissimilarity parameters are presented for curviness quantification in which using extremum point showed to achieve distinctive results. The results also show that the hexagonal image is the best image type for distinguishing the contours in the images. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.

Place, publisher, year, edition, pages
MDPI AG , 2018. Vol. 18, no 2, article id 429
Keywords [en]
Critical points, Curviness quantification, Fill factor, Grid structure, Hessian matrix, Hexagonal image, Pixel form, Software-based, Virtual, Image processing, Image sensors, Semantics, Grid structures, Hessian matrices, Pixels
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:bth-15920DOI: 10.3390/s18020429ISI: 000427544000112Scopus ID: 2-s2.0-85041511195OAI: oai:DiVA.org:bth-15920DiVA, id: diva2:1184783
Note

open access

Available from: 2018-02-22 Created: 2018-02-22 Last updated: 2018-12-20Bibliographically approved
In thesis
1. Biological Inspired Deformable Image Sensor
Open this publication in new window or tab >>Biological Inspired Deformable Image Sensor
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Nowadays, cameras are everywhere thanks to the tremendous progress on sensor technology. However, their performance is far away from what we experience by our eyes. The study from evolution process shows how the sensor arrangement of retina in human vision has differentiated from other species and is formed into a specific combination of sub-arrangements from hexagonal to elliptical ones. There are three major key differences between our visual cell arrangement and current camera sensors which are: the sub-arrangements, the pixel form and the pixel density.

Despite the advances in sensor technology we face limitations in their further development; i.e. to make the cameras close to the visual system. This is due to the optical diffraction limit which prevents us to increase the sensor resolution, and rigidity of hardware implementation which prevent us to change the image sensor after manufacturing. In the thesis the possibilities to overcome such limitations are investigated where the intention is to find a closer sensory solution to the visual system in comparison to the current ones.

Breaking the diffraction barrier and solving the rigidity problem are simultaneously achieved by introducing and estimating virtual subpixels. A statistical framework consisting of local learning model and Bayesian inference for predicting the incident photons captured on each such a subpixel is used to resample the captured image by any current camera sensor. By investigating the virtual variation of pixel size and fill factor the validity of the proposed idea is proven by which the results show significant changes of dynamic range and tonal levels in relation to the variation. As an example, for both monochrome and color images the results show that by virtual increase of fill factor to 100%, the dynamic range of the images are widened and the tonal levels are enriched significantly over 256 levels for each channel.

The results of virtual variation of the fill factor and pixel size indicates that it is feasible to change the rigidity of the image sensor using the software-based method. Inspired by the mosaic in the fovea, the center of human retina, the hexagonal sub-arrangement and pixel form are proposed to generate images based on the estimated virtual subpixels. Compared to the original square images, not only the dynamic range and tonal levels are improved, but also the hexagonal images are superior in detection of edges, i.e. more edge points on the contour of the objects are detected in hexagonal images.

The evaluation of different sub-arrangements or pixel forms of the image sensor is a challenging task and should be directed to a more specific task. Since the curvature contours contain most of the information related to object perception and human vision is highly evolved to detect curvature object, the task is focused to investigate the impact of the curviness on the different pixel forms and sub-arrangements, by comparing two categories of images; having curved versus linear edges of the objects in a pair of images which have exact similar contents but different contours. The detectability of each of the different sensor structures for curviness is estimated and the results show that the image on hexagonal grid with hexagonal pixel form is the best image type for distinguishing the curvature contours in the images.

According to the pattern of pixels tiling, there are two types of pixel sub-arrangements, i.e. periodic (e.g. square or hexagonal), and aperiodic (e.g. Penrose). Each type of sub-arrangements is investigated where the pixel forms and density are variable. By having at least two generated images of one configuration (i.e. specific sub-arrangement, pixel form and density), the result of histogram of gradient orientation of the certain sensor arrangement shows a stable and specific distribution which we called it the ANgular CHaracteristic of a sensOR structure (ANCHOR). Each ANCHOR has a robust pattern which is changed by the change of the sensor sub-arrangement. This makes it feasible to plan a sensor sub-arrangement in the relation to a specific application and its requirements, and more alike the biological vision sensory. To generate such a flexible sensor, a general framework is proposed for virtual deforming the sensor with a certain configuration of the sensor sub-arrangement, pixel form and pixel density.

Assessing the quality difference between the images generated by different sensor configuration or addressing from on configuration to another one generally needs the conversion of one to another. To overcome this problem, a common space is proposed by implementing a continuous extension of square or hexagonal images based on the orbit function, for quality evaluating the images with different arrangements and addressing from one type of image to another one. The evaluation results show that the creation of such space is feasible which facilitates a usage friendly tool to address an arrangement and assess the changes between different spatial arrangements, for example, it shows richer intensity variation, nonlinear behavior, and larger dynamic range in the hexagonal images compared to the rectangular images.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019. p. 207
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 4
Keywords
image sensor, pixel form, sub-arrangements, fill factor, square image, hexagonal image, deformable sensor, quality assessment.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-17149 (URN)978-91-7295-366-6 (ISBN)
Public defence
2019-03-14, J1650, Campus Gräsvik, Karlskrona, 13:15 (English)
Opponent
Supervisors
Available from: 2018-12-20 Created: 2018-12-20 Last updated: 2019-02-12Bibliographically approved

Open Access in DiVA

fulltext(10871 kB)22 downloads
File information
File name FULLTEXT01.pdfFile size 10871 kBChecksum SHA-512
f9e6b9c2a81517d76128e8f40e0e55541874810bbb050722fca3b86db3cdc0d792d6d8c732d1f655290bab1e2503686d1eb28e37bb426a16f35d4d64809d1bf5
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records BETA

Wen, WeiKhatibi, Siamak

Search in DiVA

By author/editor
Wen, WeiKhatibi, Siamak
By organisation
Department of Technology and Aesthetics
In the same journal
Sensors
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 22 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 24 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf