Implementation Segmentation of Color Image with Detection of Color to Detect Object
Abstract
Detection of objects in an image 2 dimensional is a process which is quite complex to do. Object detection required a computer vision approach to the desired part of the object can be recognizable computer accurately. The method in this research using waterfall method. This research will describe the application of color segmentation method with the color detection of a digital image to produce image segment object in the form of blob so that the computer can be detected. The object detection process will process the resulting color segment by the process of segmentation so that can know the number of detected objects, the area and the center of the object. This application can take pictures with laptop or notebook webcam. The result of color segmentation based on color detection is strongly influenced by color samples and color tolerance values to which the segmentation process is based. Lighting, location, texture, and contour of objects or background image will greatly affect the results of segmentation and object detection.
Keywords
Full Text:
PDFReferences
Ardhianto, E., Hadikurniawati, W., & Budiarso, Z. (2013). Implementasi Metode Image Subtracting dan Metode Regionprops untuk Mendeteksi Jumlah Objek Berwarna RGB pada File Video. Dinamik-Jurnal Teknologi Informasi, 18 (2).
Castleman, K.R. (1996). Digital image processing. Prentice Hall, New Jersey.
Forsyth, D., & Ponce, J. (2011). Computer vision: a modern approach. Upper Saddle River, NJ; London: Prentice Hall.
Giannakopoulos, T. (2008). Matlab Color Detection Software. Department of Informatics and Telecommunications, University of Athens, Greece.
Gonzalez, Rafael C., Woods, Richard E. (2001). Digital image processing. New Jersey: Prentice Hall.
Gunanto, S. G. (2009). Segmentasi Bagian Warna Tubuh Manusia pada Citra 2D. Proceeding SENTIA. Malang: Politeknik Negeri Malang
Kumaseh, M. R., Latumakulita, L., & Nainggolan, N. (2013). Segmentasi Citra Digital Ikan Menggunakan Metode Thresholding. Jurnal Ilmiah Sains, 13(1), 74-79.
Mahardika, F., Purwanto, K. A., & Saputra, D. I. S. (2017). Implementasi Metode Waterfall pada Proses Digitalisasi Citra Analog. VOLT: Jurnal Ilmiah Pendidikan Teknik Elektro, 2(1), 63-72.
Perales, F. J. (2001). Human motion analysis and synthesis using computer vision and graphics techniques. State of art and applications. In Proceedings of the 5th world multiconference on systems, cybernetics and informatics.
Rujikietgumjorn, S. (2008). Segmentation methods for multiple body parts. Knoxville: Project in lieu of Thesis University of Tennessee.
Suhendra, A. 2012. Catatan Kuliah Pengantar Pengolahan Citra Retrieved From Http://Ftp.Gunadarma.Ac.Id/Handouts/S1_Sistem%20informasi/Pengolahancitra.Pdf [Diakses 10 Januari 2017]
Wijaya, M. C., & Prijono, A. (2007). Pengolahan Citra Digital Menggunakan Matlab. Bandung: Informatika.
DOI: http://dx.doi.org/10.30870/volt.v2i2.1095
Refbacks
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
- » —
VOLT: Jurnal Ilmiah Pendidikan Teknik Elektro is licensed under a Creative Commons Attribution 4.0 International License
________________________________________________________
VOLT: Jurnal Ilmiah Pendidikan Teknik Elektro ISSN 2528-5688 (print) | ISSN 2528-5696 (online)
Published by Department of Electrical Engineering Vocational Education - Universitas Sultan Ageng Tirtayasa in collaboration with Asosiasi Dosen dan Guru Vokasi Indonesia (ADGVI) - Association of Indonesian Vocational Educators (AIVE)
Address : Jl. Ciwaru Raya No. 25, Sempu, Kota Serang, Banten 42117, Indonesia
E : [email protected], [email protected], [email protected]
Ph : +62 8566666090 / +62 81298509170