{"id":{"repo_id":"uthm","oai_identifier":"oai:eprints.uthm.edu.my:1441"},"canonical_url":"https://search.dev.ndltd.org/etd/uthm/oai:eprints.uthm.edu.my:1441","repository":{"repo_id":"uthm","name":"Universiti Tun Hussein Onn Malaysia","base_url":"http://eprints.uthm.edu.my/cgi/oai2"},"display":{"title":"Automatic red blood cell counting based on particle area","abstract":"In medical area, red blood cell (RBC) counting and analysis contributes important information in pathological diagnosis regarding disease such as anemia and low level of hemoglobin concentration. Normally the blood sample is processed in laboratory using hematology analyzer and blood smear is viewed under microscope. The analysis and counting process is conducted manually by pathologist. The task is very laborious, tedious, time-consuming and very dependent to the skill. This project applied image processing techniques to develop a computer-aided system for automated RBC counting. The RBC images will be pre-processed in early stage using morphological operations and thresholding to obtain the images with good quality. Then, the RBC images will be classified based on the particle area size into single and multi-overlap cells. For counting the total number of the RBC, mathematical numeric function is used. The accuracy of the result is determined by doing comparison with the ground truth data. The proposed method has been tested to the RBC images and performs a reliable system for counting RBC.","abstract_html":"In medical area, red blood cell (RBC) counting and analysis contributes important information in pathological diagnosis regarding disease such as anemia and low level of hemoglobin concentration. Normally the blood sample is processed in laboratory using hematology analyzer and blood smear is viewed under microscope. The analysis and counting process is conducted manually by pathologist. The task is very laborious, tedious, time-consuming and very dependent to the skill. This project applied image processing techniques to develop a computer-aided system for automated RBC counting. The RBC images will be pre-processed in early stage using morphological operations and thresholding to obtain the images with good quality. Then, the RBC images will be classified based on the particle area size into single and multi-overlap cells. For counting the total number of the RBC, mathematical numeric function is used. The accuracy of the result is determined by doing comparison with the ground truth data. The proposed method has been tested to the RBC images and performs a reliable system for counting RBC.","abstract_has_math":false,"creators":["Musa, Rabiahtuladawiyah"],"institution":"Universiti Tun Hussein Onn Malaysia","degree_name":"mphil","degree_level":"masters","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-06","date_published":"2015-06","updated_at":"2026-07-24T05:48:27Z","subjects":["TK7800-8360 Electronics"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Musa, Rabiahtuladawiyah"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-06"]},{"key":"dc:date.issued","label":"Date","values":["2015-06"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Faculty of Electrical and Electronics Engineering"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Universiti Tun Hussein Onn Malaysia"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["http://eprints.uthm.edu.my/1441/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["mphil"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["TK7800-8360 Electronics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://eprints.uthm.edu.my/1441/3/RABIAHTULADAWIAH%20MUSA%20COPYRIGHT%20DECLARATION.pdf","http://eprints.uthm.edu.my/1441/1/24p%20RABIAHTULADAWIAH%20MUSA.pdf","http://eprints.uthm.edu.my/1441/2/RABIAHTULADAWIAH%20MUSA%20WATERMARK.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In medical area, red blood cell (RBC) counting and analysis contributes important information in pathological diagnosis regarding disease such as anemia and low level of hemoglobin concentration. Normally the blood sample is processed in laboratory using hematology analyzer and blood smear is viewed under microscope. The analysis and counting process is conducted manually by pathologist. The task is very laborious, tedious, time-consuming and very dependent to the skill. This project applied image processing techniques to develop a computer-aided system for automated RBC counting. The RBC images will be pre-processed in early stage using morphological operations and thresholding to obtain the images with good quality. Then, the RBC images will be classified based on the particle area size into single and multi-overlap cells. For counting the total number of the RBC, mathematical numeric function is used. The accuracy of the result is determined by doing comparison with the ground truth data. The proposed method has been tested to the RBC images and performs a reliable system for counting RBC."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Automatic red blood cell counting based on particle area"]}]}],"canonical_facts":{"dc:creator":["Musa, Rabiahtuladawiyah"],"dc:date":["2015-06"],"dc:date.issued":["2015-06"],"dc:description.abstract":["In medical area, red blood cell (RBC) counting and analysis contributes important information in pathological diagnosis regarding disease such as anemia and low level of hemoglobin concentration. Normally the blood sample is processed in laboratory using hematology analyzer and blood smear is viewed under microscope. The analysis and counting process is conducted manually by pathologist. The task is very laborious, tedious, time-consuming and very dependent to the skill. This project applied image processing techniques to develop a computer-aided system for automated RBC counting. The RBC images will be pre-processed in early stage using morphological operations and thresholding to obtain the images with good quality. Then, the RBC images will be classified based on the particle area size into single and multi-overlap cells. For counting the total number of the RBC, mathematical numeric function is used. The accuracy of the result is determined by doing comparison with the ground truth data. The proposed method has been tested to the RBC images and performs a reliable system for counting RBC."],"dc:format":["text"],"dc:identifier.uri":["http://eprints.uthm.edu.my/1441/3/RABIAHTULADAWIAH%20MUSA%20COPYRIGHT%20DECLARATION.pdf","http://eprints.uthm.edu.my/1441/1/24p%20RABIAHTULADAWIAH%20MUSA.pdf","http://eprints.uthm.edu.my/1441/2/RABIAHTULADAWIAH%20MUSA%20WATERMARK.pdf"],"dc:language":["en"],"dc:publisher.department":["Faculty of Electrical and Electronics Engineering"],"dc:publisher.institution":["Universiti Tun Hussein Onn Malaysia"],"dc:relation.isreferencedby":["http://eprints.uthm.edu.my/1441/"],"dc:subject":["TK7800-8360 Electronics"],"dc:title":["Automatic red blood cell counting based on particle area"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["masters"],"dc:type.qualificationname":["mphil"]},"updated_at":"2026-07-24T05:48:27Z"}