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A Method for Geometrically Fixing the Distortions Originate from Perspective

Yıl 2018, Cilt: 11 Sayı: 2, 263 - 276, 31.08.2018
https://doi.org/10.18185/erzifbed.377483

Öz

Scientific expression
of depth, integrity and permanence by means of shapes and lines or camera in
areas such as image, graphic, scene decor and architecture is called
perspective. Digital imaging devices should be parallel to object to obtain
realistic images. However, objects do not seem to be parallel because of their
position. This situation causes differences between the measurements performed
on image and real object. Accurate measurement is possible only when images are
rectified. In this study, a method is proposed to correct perspective images by
the help of four different points marked by the user. In order to test the
proposed method, images are perspective distorted and corrected again through
software. The same tests were also carried out on perspective distorted images
obtained from an unknown source and successful results were obtained.

Kaynakça

  • Altıntaş, A. 2004. Dikdörtgen Kesit Alanına Sahip Bir Sargıda Uygun Sarım Tipinin Tespiti İçin Bir Yazılım. Dumlupınar Üniversitesi Fen Bilimleri Enstitüsü Dergisi, (6), 163-174.
  • Boufama, B., Habed, A. 2005. Registration and tracking in the context of augmented reality. ICGST International Journal on Graphics, Vision and Image Processing , 5(3), 9-18.
  • Clark, P., Mirmehdi, M. 2001. Estimating the Orientation and Recovery of Text Planes in a Single Image. Proceedings of the 12th British Machine Vision Conference, Manchester, UK, 421-430.
  • Clark, P., Mirmehdi, M. 2000. Location and recovery of text on oriented surfaces. SPIE conference on Document Recognition and Retrieval VII, San Jose, CA, United States, 267-277.
  • Fangi, G., Gagliardini, G., Malinverni, E. 2001. Photointerpretation and Small Scale Stereoplotting with Digitally Rectified Photographs With Geometrical Constraints. Cipa 2001 XVIII International Symposium, Potsdam, Germany, 160-167.
  • Huang, J., Boufama, B. 2002. A semi-automatic camera calibration method for augmented reality. IEEE International Conference on Systems, Man, and Cybernetics, Hammamet, Tunisia, 700-705.
  • Karaca, N. 2007. Alçak Çözünürlüklü Fotoğrafların Görüntülenmesi ve Bunların Optimizasyonu İle İlgili Bir Çalışma. Yüksek Lisans Tezi, Ege Üniversitesi Fen Bilimleri Enstitüsü. İzmir.
  • Li, X., Liu, W., Fan, W., Sun, J, Satoshi, N. 2016. Perspective correction using camera intrinsic parameters. 13th International Conference on Signal Processing (ICSP), Chengdu, China, 854-858.
  • Mirmehdi, M., Clark, P. 2000. Location and recovery of text on oriented surfaces. Document Recognition and Retrieval VII , 267-277.
  • Mohan, S., Avinash, N., Murali, S. 2013. Rectification of Perspective distortion using camera parameters -A Perspective Geometry Based Approach. ICGST International Journal on Graphics,Vision and Image Processing, 8(1), 1-7.
  • Phan, T.Q., Shivakumara, P., Tian, S., Tan, C.L. 2013. Recognizing Text with Perspective Distortion in Natural Scenes. IEEE International Conference on Computer Vision, Sydney, NSW, Australia, 569-576.
  • Pilu, M. 2001. Deskewing perspectively distorted documents: An approach based on perceptual organization. HPL-2001-100, HP Labs Technical Reports, Bristol.
  • Spitschan, B., Ostermann, J. 2017. Estimation of radial distortion using local spectra of planar textures. Fifteenth IAPR International Conference on Machine Vision Applications (MVA), Agoya, Japan, 472-477
  • Takezawa, Y., Hasegawa, M., Tabbone, S. 2016. Camera-captured document image perspective distortion correction using vanishing point detection based on Radon transform. 23rd International Conference on Pattern Recognition (ICPR), Cancun, Mexico, 3968-3974.
  • Tasdemir, S., Urkmez, A., Inal, S. 2011. Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis. Computers and Electronics in Agriculture (ISI), 76(2), 189–197.
  • Taşdemir, Ş., Ürkmez, A., İnal, Ş. 2011. A fuzzy rule-based system for predicting the live weight of Holstein cows whose body dimensions were determined by image analysis. Turkish Journal of Electrical Engineering and Computer Sciences (ISI) , 19(4), 689-703.
  • Taşdemir, Ş., Ürkmez, A., Yakar, M., İnal, Ş. 2009. Sayısal Görüntü Analiz İşleminde Kamera Kalibrasyon Parametrelerinin Belirlenmesi. 5. Uluslararası İleri Teknolojiler Sempozyumu (IATS’09), Karabük, Türkiye, 87-92.
  • Ulges, A., Lampert, C., Breuel, T. 2005. Document Image Dewarping using Robust Estimation of Curled Text Lines. International Conference on Document Analysis and Recognition (ICDAR), Seoul, Korea, 1001-1005.
  • Ünsal, F.B. 2009. İki Boyutlu Doğrusal Koordinat Dönüşümleri. TMMOB Harita ve Kadastro Mühendisleri Odası 12. Türkiye Harita Bilimsel ve Teknik Kurultayı, Ankara.
  • Wang, X., Klette, R., Rosenhahn, B. 2005. Geometric and photometric correction of projected rectangular pictures. Image and Vision Computing, New Zealand, 223-228.
  • Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.P. 2004. Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing , 13(4), 600-612.
  • Weng, J., Cohen, P., Herniou, M. 1992. Camera Calibration with Distortion Models and Accuracy Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(10), 965-980.
  • Yan, W., Hou, C. 2016. Reducing perspective distortion for stereoscopic image stitching. IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Seattle, WA, USA, 1-6.
  • Zhou, L., Deng, Z. 2014. Perspective distortion rectification for planar object based on LIDAR and camera data fusion. 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), Qingdao, China, 270-275.

Perspektiften Kaynaklanan Bozulmaların Geometrik Olarak Düzeltilmesi İçin Bir Yöntem

Yıl 2018, Cilt: 11 Sayı: 2, 263 - 276, 31.08.2018
https://doi.org/10.18185/erzifbed.377483

Öz

Resim,
grafik, sahne dekoru ve mimarlık gibi alanlarda derinliğin, bütünlüğün,
devamlılığın, biçim ve çizgilerle ya da fotoğraf makinesi aracılığıyla bilimsel
olarak ifade edilmesine perspektif adı verilmektedir. Gerçekçi görüntüler elde
edilebilmek için sayısal görüntüleme aygıtları nesneye paralel olmalıdır. Ancak
nesneler konumları yüzünden her zaman bu paralelliği göstermez. Bu durum
görüntü üzerinden yapılan ölçmeler ile gerçek ölçüler arasında farka neden
olur. Doğru ölçümlerin yapılabilmesi ancak perspektif görüntülerin düzeltilmesi
ile mümkündür. Bu çalışmada, kullanıcı tarafından işaretlenen dört farklı nokta
yardımıyla perspektif görüntülerin düzeltilmesini sağlayan bir yöntem
önerilmiştir. Önerilen yöntemin test edilebilmesi için bir yazılım aracılığı
ile görüntüler perspektif olarak bozulmuş ve tekrar düzeltilmiştir. Aynı
testler kaynağı belli olmayan perspektif bozulmuş görüntüler üzerinde de
gerçekleştirilmiş ve başarılı sonuçlar elde edilmiştir
.  

Kaynakça

  • Altıntaş, A. 2004. Dikdörtgen Kesit Alanına Sahip Bir Sargıda Uygun Sarım Tipinin Tespiti İçin Bir Yazılım. Dumlupınar Üniversitesi Fen Bilimleri Enstitüsü Dergisi, (6), 163-174.
  • Boufama, B., Habed, A. 2005. Registration and tracking in the context of augmented reality. ICGST International Journal on Graphics, Vision and Image Processing , 5(3), 9-18.
  • Clark, P., Mirmehdi, M. 2001. Estimating the Orientation and Recovery of Text Planes in a Single Image. Proceedings of the 12th British Machine Vision Conference, Manchester, UK, 421-430.
  • Clark, P., Mirmehdi, M. 2000. Location and recovery of text on oriented surfaces. SPIE conference on Document Recognition and Retrieval VII, San Jose, CA, United States, 267-277.
  • Fangi, G., Gagliardini, G., Malinverni, E. 2001. Photointerpretation and Small Scale Stereoplotting with Digitally Rectified Photographs With Geometrical Constraints. Cipa 2001 XVIII International Symposium, Potsdam, Germany, 160-167.
  • Huang, J., Boufama, B. 2002. A semi-automatic camera calibration method for augmented reality. IEEE International Conference on Systems, Man, and Cybernetics, Hammamet, Tunisia, 700-705.
  • Karaca, N. 2007. Alçak Çözünürlüklü Fotoğrafların Görüntülenmesi ve Bunların Optimizasyonu İle İlgili Bir Çalışma. Yüksek Lisans Tezi, Ege Üniversitesi Fen Bilimleri Enstitüsü. İzmir.
  • Li, X., Liu, W., Fan, W., Sun, J, Satoshi, N. 2016. Perspective correction using camera intrinsic parameters. 13th International Conference on Signal Processing (ICSP), Chengdu, China, 854-858.
  • Mirmehdi, M., Clark, P. 2000. Location and recovery of text on oriented surfaces. Document Recognition and Retrieval VII , 267-277.
  • Mohan, S., Avinash, N., Murali, S. 2013. Rectification of Perspective distortion using camera parameters -A Perspective Geometry Based Approach. ICGST International Journal on Graphics,Vision and Image Processing, 8(1), 1-7.
  • Phan, T.Q., Shivakumara, P., Tian, S., Tan, C.L. 2013. Recognizing Text with Perspective Distortion in Natural Scenes. IEEE International Conference on Computer Vision, Sydney, NSW, Australia, 569-576.
  • Pilu, M. 2001. Deskewing perspectively distorted documents: An approach based on perceptual organization. HPL-2001-100, HP Labs Technical Reports, Bristol.
  • Spitschan, B., Ostermann, J. 2017. Estimation of radial distortion using local spectra of planar textures. Fifteenth IAPR International Conference on Machine Vision Applications (MVA), Agoya, Japan, 472-477
  • Takezawa, Y., Hasegawa, M., Tabbone, S. 2016. Camera-captured document image perspective distortion correction using vanishing point detection based on Radon transform. 23rd International Conference on Pattern Recognition (ICPR), Cancun, Mexico, 3968-3974.
  • Tasdemir, S., Urkmez, A., Inal, S. 2011. Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis. Computers and Electronics in Agriculture (ISI), 76(2), 189–197.
  • Taşdemir, Ş., Ürkmez, A., İnal, Ş. 2011. A fuzzy rule-based system for predicting the live weight of Holstein cows whose body dimensions were determined by image analysis. Turkish Journal of Electrical Engineering and Computer Sciences (ISI) , 19(4), 689-703.
  • Taşdemir, Ş., Ürkmez, A., Yakar, M., İnal, Ş. 2009. Sayısal Görüntü Analiz İşleminde Kamera Kalibrasyon Parametrelerinin Belirlenmesi. 5. Uluslararası İleri Teknolojiler Sempozyumu (IATS’09), Karabük, Türkiye, 87-92.
  • Ulges, A., Lampert, C., Breuel, T. 2005. Document Image Dewarping using Robust Estimation of Curled Text Lines. International Conference on Document Analysis and Recognition (ICDAR), Seoul, Korea, 1001-1005.
  • Ünsal, F.B. 2009. İki Boyutlu Doğrusal Koordinat Dönüşümleri. TMMOB Harita ve Kadastro Mühendisleri Odası 12. Türkiye Harita Bilimsel ve Teknik Kurultayı, Ankara.
  • Wang, X., Klette, R., Rosenhahn, B. 2005. Geometric and photometric correction of projected rectangular pictures. Image and Vision Computing, New Zealand, 223-228.
  • Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.P. 2004. Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing , 13(4), 600-612.
  • Weng, J., Cohen, P., Herniou, M. 1992. Camera Calibration with Distortion Models and Accuracy Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(10), 965-980.
  • Yan, W., Hou, C. 2016. Reducing perspective distortion for stereoscopic image stitching. IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Seattle, WA, USA, 1-6.
  • Zhou, L., Deng, Z. 2014. Perspective distortion rectification for planar object based on LIDAR and camera data fusion. 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), Qingdao, China, 270-275.
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Erdal Güvenoğlu

Yayımlanma Tarihi 31 Ağustos 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 11 Sayı: 2

Kaynak Göster

APA Güvenoğlu, E. (2018). Perspektiften Kaynaklanan Bozulmaların Geometrik Olarak Düzeltilmesi İçin Bir Yöntem. Erzincan University Journal of Science and Technology, 11(2), 263-276. https://doi.org/10.18185/erzifbed.377483