BZPEERPapers, people, evidence and research paths
Menu

Discover

SearchFind papers, people, topics, institutions and opportunities from one place.GraphSee how papers, authors, topics and evidence connect.

Research tools

HomeContinue from the papers, people and topics that matter now.CollectionsTurn saved papers into reading lists, evidence maps and shareable context.ResearchReconstruct the path that led you from search to paper to question.CollaborationMove from a paper, topic or expert request into a focused thread.PublishCreate full-text research articles with metadata, formulas and versions.

Network

ExpertsFind specialists whose work and reviews explain why they can help.CommunitiesJoin research groups organized around papers, topics and shared evidence.

Opportunities

ListingsBrowse roles, calls and collaborations connected to real research context.

Account

Log inReturn to your saved papers, graph views and active threads.Create accountStart saving papers, building a research trail and joining teams.
Log inCreate account

Paper detail

Color-Coded Symbology and New Computer Vision Tool to Predict the Historical Color Pallets of the Renaissance Oil Artworks

In this paper, we discuss possible color palletes, prediction and analysis of originality of the colors that Artists used on the Renaissance oil paintings. This framework goal is to help to use the color symbology and image enhancement tools, to predict the historical color palletes of the Renaissance oil artworks. This work is only the start of a development to explore the possibilities of prediction of color palletes of the Renaissance oil artworks. We believe that framework might be very useful in the prediction of color palletes of the Renaissance oil artworks and other artworks. The images in number 105 have been taken from the paintings of three well-known artists, Rafael, Leonardo Da Vinci, and Rembrandt that are available in the Olga's Gallery. Images are processed in the frequency domain to enhance a quality of images and ratios of primary colors are calculated and analyzed by using new measurements of color-ratios.

preprint2021arXivOpen access
Artyom M. GrigoryanSos S. Agaian
Computer Vision
Open graphReviewsDiscussion

Signal facts

What is known right now

Open access2 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

Next steps

Decide what to do with this paper

Like0Dislike0Score 0

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Save to reading list0
Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Authors

Artyom M. GrigoryanSos S. Agaian

Institutions

No institution affiliation has been imported for this paper yet.

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form
Log in to review

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form
Log in to comment

No discussion yet. The first strong comment sets the tone.