[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128127-en":3,"doc-seo-128127-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},128127,3985741905716,"Rowan","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","A Hair Drawing Evaluation Algorithm for Exactness Assessment Method in Portrait Drawing Learning Assistant System","Portrait drawing is widely used to develop artistic skills and emotional expression, yet beginners struggle to grasp facial proportions and structural foundations. Portrait Drawing Learning Assistant System (PDLAS) guides learners using auxiliary facial feature lines generated with OpenPose and OpenCV. An exactness assessment method evaluates drawing accuracy via Normalized Cross-Correlation (NCC) similarity between user drawings and the initial portrait photo. The method lacked hair assessment, though hair largely influences portrait quality; this work introduces a hair evaluation algorithm extracting hair texture from eigenvalues and eigenvectors, validated on student drawing results and improving NCC scores.","algorithms   \nArticle  \nA Hair Drawing Evaluation Algorithm for Exactness Assessment Method in Portrait Drawing Learning Assistant System  \nYue Zhang 1, Nobuo Funabiki 1,*, Erita Cicilia Febrianti 2, Amang Sudarsono 2 and Chenchien Hsu 3  \nAcademic Editor: BinlinZhang  \nReceived: 3 January 2025  \nRevised: 20 February 2025  \nAccepted: 24 February 2025  \nPublished: 4 March 2025  \nCitation: Zhang , Y.; Funabiki, N.; Febrianti, E.C.; Sudarsono, A.; Hsu, C. A Hair Drawing Evaluation Algorithm for Exactness Assessment Method in Portrait Drawing Learning Assistant System. Algorithms 2025, 18, 143. [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)a18030143  \nCopyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://creativecommons.org/](https://creativecommons.org/)[ ](https://creativecommons.org/)[licenses/by/4.0/](licenses/by/4.0/)) .  \n1 Department of Information and Communication Systems, Okayama University, Okayama 700-8530, Japan; [pr1u5yrh@s.okayama-u.ac.jp](pr1u5yrh@s.okayama-u.ac.jp)  \n2 Department of Electrical Engineering, Politeknik Elektronika Negeri Surabaya, Surabaya 60111, Indonesia; [erita.cici17@gmail.com](erita.cici17@gmail.com) (E.C.F.); [amang@pens.ac.id](amang@pens.ac.id) (A.S.)  \n3 Department of Electrical Engineering, National Taiwan Normal University, Taipei 106308, Taiwan; [jhsu@ntnu.edu.tw](jhsu@ntnu.edu.tw)  \n* Correspondence: [funabiki@okayama-u.ac.jp](funabiki@okayama-u.ac.jp)  \nAbstract: Nowadays, portrait drawing has become increasingly popular as a means of developing artistic skills and nurturing emotional expression. However, it is challenging for novices to start learning it, as they usually lack a solid grasp of proportions and structural foundations of the five senses. To address this problem, we have studied Portrait Drawing Learning Assistant System (PDLAS) for guiding novices by providing auxiliary lines of facial features, generated by utilizing OpenPose and OpenCV libraries. For PDLAS, we have also presented the exactness assessment method to evaluate drawing accuracy using the Normalized Cross-Correlation (NCC) algorithm. It calculates the similarity score between the drawing result and the initial portrait photo. Unfortunately, the current method does not assess the hair drawing, although it occupies a large part of a portrait and often determinesits quality. In this paper, we present a hair drawing evaluation algorithm for the exactness assessment method to offer comprehensive feedback to users in PDLAS. To emphasize hairlines, this algorithm extracts the texture of the hair region by computing the eigenvaluesand eigenvectors of the hair image. For evaluations, we applied the proposal to drawing results by seven students from Okayama University, Japan and confirmed the validity. In addition, we observed the NCC score improvement in PDLAS by modifying the face parts with low similarity scores from the exactness assessment method.  \nKeywords: portrait drawing; auxiliary lines; OpenPose; OpenCV; normalized cross-correlation (NCC); hair texture; exactness assessment method  \n1. Introduction  \nNowadays, the practice of portrait drawing has become increasingly popular as a means of fostering artistic talent and empathy [1] . Despite its widespread popularity, portrait drawing remains challenging, especially for novices. They frequently find it difficult to understand the proportions and structure of facial features without professional helps [2] . To address this problem, we have studied and implemented Portrait Drawing Learning Assistant System (PDLAS) to guide beginners in drawing a portrait by providing the auxiliary lines of facial features [3] . OpenPose [4] and OpenCV [5] libraries are used together to construct and integrate the auxiliary lines from a given face photo. In PDLAS, an iPad device is supposed to ","cbCaihJghOhcCWw0","https://ap.wps.com/l/cbCaihJghOhcCWw0","pdf",7895132,2,1,17,"English","en",105,"# Introduction\n## Portrait Drawing Learning Assistant System (PDLAS)\n## Exactness assessment with NCC\n## Proposed hair drawing evaluation algorithm\n# Related works\n# System overview (PDLAS)\n# Hair evaluation method and bounding-box extraction\n# Experiments and validity evaluation","[{\"question\":\"What problem does the paper address in portrait drawing for beginners?\",\"answer\":\"Beginners find it difficult to understand facial proportions and structure without professional guidance. The paper targets this by supporting learners with PDLaS and feedback based on similarity evaluation.\"},{\"question\":\"How does PDLAS assess drawing accuracy?\",\"answer\":\"PDLAS computes similarity scores using the Normalized Cross-Correlation (NCC) algorithm between bounding boxes of facial parts in the user drawing and the original portrait photo.\"},{\"question\":\"How does the proposed method evaluate hair drawing accuracy?\",\"answer\":\"The method emphasizes hairlines by extracting hair texture features from the hair region using eigenvalues and eigenvectors, then applying these features within the NCC-based exactness assessment.\"}]","A Hair Drawing Evaluation Algorithm for Exactness Assessment Method in Portrait Drawing Learning Assistant System | PDF",1785944975,43,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"a-hair-drawing-evaluation-algorithm-for-exactness-assessment-method-in-portrait-drawing-learning-assistant-system","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/a-hair-drawing-evaluation-algorithm-for-exactness-assessment-method-in-portrait-drawing-learning-assistant-system/128127/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-22","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the paper address in portrait drawing for beginners?","Question",{"text":76,"@type":77},"Beginners find it difficult to understand facial proportions and structure without professional guidance. The paper targets this by supporting learners with PDLaS and feedback based on similarity evaluation.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How does PDLAS assess drawing accuracy?",{"text":81,"@type":77},"PDLAS computes similarity scores using the Normalized Cross-Correlation (NCC) algorithm between bounding boxes of facial parts in the user drawing and the original portrait photo.",{"name":83,"@type":74,"acceptedAnswer":84},"How does the proposed method evaluate hair drawing accuracy?",{"text":85,"@type":77},"The method emphasizes hairlines by extracting hair texture features from the hair region using eigenvalues and eigenvectors, then applying these features within the NCC-based exactness assessment.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]