About

Erciyes University Campus

Erciyes University Computer Vision Laboratory (ERU.Vision) is part of the Computer Engineering Department at Erciyes University. Research in our lab focuses on developing intelligent algorithms that perform important visual perception tasks such as object recognition, image fusion, scene understanding, pattern recognition etc.

People

aslantas

Prof. Dr. Veysel ASLANTAŞ

Faculty


aslantas@erciyes.edu.tr


ozturk

Dr. Serkan ÖZTÜRK

Faculty


serkan@erciyes.edu.tr


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Dr. Ahmet Nusret TOPRAK

Faculty


antoprak@erciyes.edu.tr


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Ersin KILIÇ

PhD Candidate


ersinkilic@erciyes.edu.tr


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Ertuğrul GÜL

PhD Candidate


blank@erciyes.edu.tr


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Ömer Faruk SARITAŞ

PhD Candidate


blank@erciyes.edu.tr


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Asiye ULAŞ

PhD Candidate


blank@erciyes.edu.tr


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Mehmet ELMACI

PhD Candidate


blank@erciyes.edu.tr


Research

Realtime Color Analysis and Faulty Detection Over Wet Sugar

Ministry of Science, Industry and Technology - Industrial Theses Supporting Program (San-Tez) Award: 0868.STZ.2015

Sugar producing process includes centrifuging, massecuite gathering, washing, drying and packaging steps. Sugar producing process steps in this framework can be explained like this: The device that separates the sugar and syrup in the massecuite using the centrifugal force is called centrifuge and this process is called centrifuging. Working principle is discontinuous. Massecuite is being periodically centrifuge, during the centrifuging, syrup and crystal particles separate. The separated crystal sugar in the centrifuge is discharged into helical transportation system. Massecuite is put into empty centrifuge over again and same process repeats. Massecuite gathering processes are massecuite insertion (filling), speeding, maximum speed centrifuging, removing and cleaning of centrifuge filter. During massecuite centrifuging, syrup that primarily obtained has low purity and green color. During washing process, wash water dissolves a little sugar and because of this, the syrup with purity that higher than green syrup, is called white syrup. Separated crystal sugar is sent to drying unit as selling sugar. Sliding lower lid opens at the start of crystal sugar discharging from centrifuge and becomes closed at the end of the mission. Color analysis system that is planned to design within Project, takes place in this step as to decide sending predrying sugar to packaging or melting. Subject product of Project, provides the detection of yellow sugar that is called faulty sugar and transferring back to pan. Thus, yellow sugar can be processed without interfering with selling quality sugar. On the other hand, sugar color measurements that made in the laboratory according to ICUMSA Standard (International Commission for Uniform Methods of Sugar Analysis), can be done in the production environment with realtime. Color analysis system takes images from suitable parts of production line that works with helical transportation system technique. Color analysis is made by processing the frequentative acquired images. If critical color change occurs, faulty product lid will open and that will provide inclusion of the faulty sugar to production again. All analysis results and exceptional circumstances that occur can be viewed real time and saved to database. By this means, color analysis survey made in the laboratory, can be executed over wet sugar.


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Publication

Journal Publications

  • Aslantaş V., Kurban R., Toprak A.N., Bendeş E., "An Interactive Web Based Toolkit For Multi Focus Image Fusion", Journal of Web Engineering, vol.14, no.1 & 2, pp.117-135, 2015
  • Aslantaş V., Toprak A.N., "A Pixel Based Multi-Focus Image Fusion Method", Optics Communications, vol.332, pp.350-358, 2014 link
  • Aslantaş V., Bendeş E., Kurban R., Toprak A.N., "New Optimised Region-Based Multi-Scale Image Fusion Method For Thermal And Visible Images", IET IMAGE PROCESSING, vol.8, pp.289-299, 2014 link
  • Kurban T., Çivicioğlu Beşdok P., Kurban R., Beşdok E., "Comparison Of Evolutionary And Swarm Based Computational Techniques For Multilevel Color Image Thresholding", APPLIED SOFT COMPUTING, vol.23, pp.128-143, 2014
  • Kiliç K., Er Ö., Kilinç H.İ., Aslan T., Bendeş E., Şekerci A.E., Aslantaş V., "Infrared Thermographic Comparison Of Temperature Increases On The Root Surface During Dowel Space Preparations Using Circular Versus Oval Fiber Dowel Systems", Journal of Prosthodontics, vol.21, pp.203-207, 2012 link
  • Aslantaş V., Kurban R., "Fusion Of Multi-Focus Images Using Differential Evolution Algorithm", EXPERT SYSTEMS WITH APPLICATIONS, vol.37, pp.8861-8870, 2010 link
  • Aslantaş V., Kurban R., "A Comparison Of Criterion Functions For Fusion Of Multi-Focus Noisy Images", OPTICS COMMUNICATIONS, vol.282, pp.3231-3242, 2009 link
  • Aslantaş V., "An Optimal Robust Digital Image Watermarking Based On Svd Using Differential Evolution Algorithm", OPTICS COMMUNICATIONS, vol.282, pp.769-777, 2009 link
  • Aslantaş V., Özer Ş., Öztürk S., "Improving The Performance Of Dct-Based Fragile Watermarking Using Intelligent Optimization Algorithms", OPTICS COMMUNICATIONS, vol.282, pp.2806-2817, 2009
  • Aslantaş V., "A Singular-Value Decomposition-Based Image Watermarking Using Genetic Algorithm", AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, vol.62, pp.386-394, 2008
  • Aslantaş V., Kurban R., Çağlikantar T., "Using Digital Signatures In Wireless Portable Remote Health Monitoring Systems", J. FAC. ENG. ARCH. GAZI UNIV., vol.23, pp.531-538, 2008
  • Aslantaş V., Pham D.T., "Depth From Automatic Defocusing", OPTICS EXPRESS, vol.15, pp.1011-1023, 2007
  • Aslantaş V., "A Depth Estimation Algorithm With A Single Image", OPTICS EXPRESS, vol.15, pp.5024-5029, 2007