{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/21186"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/21186","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A trainable image pattern classification system for detection of damaged soybean seeds","abstract":"Optical properties of asymptomatic soybean seeds, green seeds, and four classes of soybean seeds discolored by fungi were determined using a spectroradiometer. Knowledge of the optical properties of soybean seeds provided a means of identifying that differences in spectral reflectance existed which could be used for discriminating among asymptomatic soybean seeds and seeds discolored by a pathogen. This knowledge also aided in identifying the feasibility of using color filters as a means for separation of soybean seed classes. Electromagnetic radiation between 436 and 724 nm provided the most information for linear separation of soybean seeds which was useful for identifying differences in the colors of soybean seeds. No single wavelength or combination of wavelengths could be used to linearly separate all classes of soybean seeds. The camera was used without modification by filters to collect data representing soybeans from the entire visible spectrum.","abstract_html":"Optical properties of asymptomatic soybean seeds, green seeds, and four classes of soybean seeds discolored by fungi were determined using a spectroradiometer. Knowledge of the optical properties of soybean seeds provided a means of identifying that differences in spectral reflectance existed which could be used for discriminating among asymptomatic soybean seeds and seeds discolored by a pathogen. This knowledge also aided in identifying the feasibility of using color filters as a means for separation of soybean seed classes. Electromagnetic radiation between 436 and 724 nm provided the most information for linear separation of soybean seeds which was useful for identifying differences in the colors of soybean seeds. No single wavelength or combination of wavelengths could be used to linearly separate all classes of soybean seeds. The camera was used without modification by filters to collect data representing soybeans from the entire visible spectrum.","abstract_has_math":false,"creators":["Casady, William Walter"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Agricultural Engineering","degree_department":null,"school":null,"contributors":["Paulsen, Marvin R."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T13:00:58Z","date_published":"2011-05-07T13:00:58Z","updated_at":"2026-07-22T22:25:17Z","subjects":["Engineering, Agricultural","Engineering, Electronics and Electrical","Computer Science"],"languages":["eng"],"rights":["Copyright 1991 Casady, William Walter"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9210758","(UMI)AAI9210758"],"render_values":[{"text":"AAI9210758","href":null,"code":true},{"text":"(UMI)AAI9210758","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/21186","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Paulsen, Marvin R."]},{"key":"dc:creator","label":"Author","values":["Casady, William Walter"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T13:00:58Z","10000-01-01","1991"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Agricultural","Engineering, Electronics and Electrical","Computer Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1991 Casady, William Walter"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9210758","(UMI)AAI9210758","http://hdl.handle.net/2142/21186"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Optical properties of asymptomatic soybean seeds, green seeds, and four classes of soybean seeds discolored by fungi were determined using a spectroradiometer. Knowledge of the optical properties of soybean seeds provided a means of identifying that differences in spectral reflectance existed which could be used for discriminating among asymptomatic soybean seeds and seeds discolored by a pathogen. This knowledge also aided in identifying the feasibility of using color filters as a means for separation of soybean seed classes. Electromagnetic radiation between 436 and 724 nm provided the most information for linear separation of soybean seeds which was useful for identifying differences in the colors of soybean seeds. No single wavelength or combination of wavelengths could be used to linearly separate all classes of soybean seeds. The camera was used without modification by filters to collect data representing soybeans from the entire visible spectrum.","\"An image pattern classification program was developed to discriminate among asymptomatic soybean seeds, immature seeds and seeds that had been discolored by fungi or a virus. The program was trainable and could be retrained by the user by recording images of exemplars while using a training mode. The algorithm used chromaticity coordinates to correctly classify asymptomatic seeds, seeds infected by C. kikuchii, seeds which belong to a group used by the Federal Grain Inspection Service called \"\"seeds of other colors\"\", and \"\"materially damaged seeds\"\" 94.3%, 97.3%, 85.3%, and 95.9% of the time, respectively. The comprehensive results for all tests yielded a classification accuracy of 93.9% for classification of seeds into classes which conformed to USDA/FGIS grading procedures. The variables used for classification were color, which was expressed using chromaticity coordinates, and seed shape which was estimated using sphericity. The decision function provided a consistent method and a viable alternative for quality inspection of soybean seeds based on color and sphericity. The computer program was easily adaptable to other seeds by retraining.\"","Made available in DSpace on 2011-05-07T13:00:58Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9210758.pdf: 6052589 bytes, checksum: 7ad5f1d400a72642518291a53a865153 (MD5) Previous issue date: 1991","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:49:04Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:22:17-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"]},{"key":"dc:title","label":"Title","values":["A trainable image pattern classification system for detection of damaged soybean seeds"]}]}],"canonical_facts":{"dc:contributor":["Paulsen, Marvin R."],"dc:creator":["Casady, William Walter"],"dc:date":["2011-05-07T13:00:58Z","10000-01-01","1991"],"dc:description":["Optical properties of asymptomatic soybean seeds, green seeds, and four classes of soybean seeds discolored by fungi were determined using a spectroradiometer. Knowledge of the optical properties of soybean seeds provided a means of identifying that differences in spectral reflectance existed which could be used for discriminating among asymptomatic soybean seeds and seeds discolored by a pathogen. This knowledge also aided in identifying the feasibility of using color filters as a means for separation of soybean seed classes. Electromagnetic radiation between 436 and 724 nm provided the most information for linear separation of soybean seeds which was useful for identifying differences in the colors of soybean seeds. No single wavelength or combination of wavelengths could be used to linearly separate all classes of soybean seeds. The camera was used without modification by filters to collect data representing soybeans from the entire visible spectrum.","\"An image pattern classification program was developed to discriminate among asymptomatic soybean seeds, immature seeds and seeds that had been discolored by fungi or a virus. The program was trainable and could be retrained by the user by recording images of exemplars while using a training mode. The algorithm used chromaticity coordinates to correctly classify asymptomatic seeds, seeds infected by C. kikuchii, seeds which belong to a group used by the Federal Grain Inspection Service called \"\"seeds of other colors\"\", and \"\"materially damaged seeds\"\" 94.3%, 97.3%, 85.3%, and 95.9% of the time, respectively. The comprehensive results for all tests yielded a classification accuracy of 93.9% for classification of seeds into classes which conformed to USDA/FGIS grading procedures. The variables used for classification were color, which was expressed using chromaticity coordinates, and seed shape which was estimated using sphericity. The decision function provided a consistent method and a viable alternative for quality inspection of soybean seeds based on color and sphericity. The computer program was easily adaptable to other seeds by retraining.\"","Made available in DSpace on 2011-05-07T13:00:58Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9210758.pdf: 6052589 bytes, checksum: 7ad5f1d400a72642518291a53a865153 (MD5) Previous issue date: 1991","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:49:04Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:22:17-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"],"dc:identifier":["AAI9210758","(UMI)AAI9210758","http://hdl.handle.net/2142/21186"],"dc:language":["eng"],"dc:rights":["Copyright 1991 Casady, William Walter"],"dc:subject":["Engineering, Agricultural","Engineering, Electronics and Electrical","Computer Science"],"dc:title":["A trainable image pattern classification system for detection of damaged soybean seeds"],"dc:type":["text"],"thesis:degree_discipline":["Agricultural Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:17Z"}