Performance Evaluation and Comparison of Service-based Image Processing based on Software Rendering

Wegen, Ole; Trapp, Matthias; Döllner, Jürgen; Pasewaldt, Sebastian

doi:10.24132/csrn.2019.2901.1.15

Cited by 3 publications

(2 citation statements)

References 29 publications

(31 reference statements)

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“…Server-side implementation based on microservices have the advantage of increased scalability, easy deployment and maintainability as well as, the possibility to introduce various technologies into one system [24]. However, high update latencies limit their usage in realtime applications [21,25]. Therefore, we favor the integration of client-side processing for our approach by developing a WebGL-based image processor.…”

Section: Image Processing As a Servicementioning

confidence: 99%

CERVI: collaborative editing of raster and vector images

et al. 2022

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Various web-based image-editing tools and web-based collaborative tools exist in isolation. Research focusing to bridge the gap between these two domains is sparse. We respond to the above and develop prototype groupware for real-time collaborative editing of raster and vector images in a web browser. To better understand the requirements, we conduct a preliminary user study and establish communication and synchronization as key elements. The existing groupware for text documents or presentations handles the above through well-established techniques. However, those cannot be extended as it is for raster or vector graphics manipulation. To this end, we develop a document model that is maintained by a server and is delivered and synchronized to multiple clients. Our prototypical implementation is based on a scalable client–server architecture: using WebGL for interactive browser-based rendering and WebSocket connections to maintain synchronization. We evaluate our work qualitatively through a post-deployment user study for three different scenarios. For quantitative evaluation, we perform a thorough performance measure on both client and server side, thereby identifying design recommendations for future concurrent image-editing software(s).

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Section: Image Processing As a Servicementioning

confidence: 99%

CERVI: collaborative editing of raster and vector images

et al. 2022

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“…For our work, we are extending a microservice platform for cloud-based visual analysis and processing that was first presented by Richter et al [16]. Based on that, Wegen et al [19] present an approach for performing service-based image processing using software rendering to balance cost-performance relation. The presented service-based application for image processing is primarily used to stylize photos.…”

Section: Microservice Infrastructuresmentioning

confidence: 99%

Service-based Processing of Gigapixel Images

Fregien¹,

Pasewaldt²,

Döllner³

et al. 2021

CSRN

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With the ongoing improvement of digital cameras and smartphones, more and more people can acquire high- resolution digital images. Due to their size and high performance requirements, such Gigapixel Images (GPIs) are often challenging to process and explore compared to conventional low resolution images. To address this problem, this paper presents a service-based approach for GPI processing in a device-independent way using cloud-based processing. For it, the concept, design, and implementation of GPI processing functionality into service-based architectures is presented and evaluated with respect to advantages, limitations, and runtime performance.

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Service-based Processing of Gigapixel Images

Fregien¹,

Pasewaldt²,

Döllner³

et al. 2021

CSRN

Self Cite

View full text Add to dashboard Cite

With the ongoing improvement of digital cameras and smartphones, more and more people can acquire high-resolution digital images. Due to their size and high performance requirements, such Gigapixel Images (GPIs) areoften challenging to process and explore compared to conventional low resolution images. To address this problem,this paper presents a service-based approach for GPI processing in a device-independent way using cloud-basedprocessing. For it, the concept, design, and implementation of GPI processing functionality into service-basedarchitectures is presented and evaluated with respect to advantages, limitations, and runtime performance.

show abstract

Performance Evaluation and Comparison of Service-based Image Processing based on Software Rendering

Cited by 3 publications

References 29 publications

CERVI: collaborative editing of raster and vector images

CERVI: collaborative editing of raster and vector images

Service-based Processing of Gigapixel Images

Service-based Processing of Gigapixel Images

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