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dc.contributor.authorRaviya, Kapil-
dc.contributor.authorVyas, Ved-
dc.contributor.authorKothari, Ashish-
dc.contributor.authorGohil, Gunvantsinh-
dc.date.accessioned2023-05-18T02:45:10Z-
dc.date.available2023-05-18T02:45:10Z-
dc.date.issued2019-
dc.identifier.citationRaviya, K. ,Vyas, V. ,Kothari, A. ,and Gohil, G.(2019). Real Time Depth Hole Filling using Kinect Sensor and Depth Extract from Stereo Images, Oriental Journal of Computer Science and Technology, ISSN: 0974-6471, Vol. 12, No. (3) 2019, Pg. 115-122. https://www.computerscijournal.org/vol12no3/real-time-depth-hole-filling-using-kinect-sensor-and-depth-extract-from-stereo-images/en_US
dc.identifier.issn0974-6471-
dc.identifier.urihttp://10.9.150.37:8080/dspace//handle/atmiyauni/1000-
dc.descriptionThe authors wish to express their gratitude to the Principal and Dean, College of Agricultural Engineering and Technology, Junagadh Agricultural University, Junagadh India for providing valuable guidance and other facilities for preparation of this manuscript.en_US
dc.description.abstractThe researcher have suggested real time depth based on frequency domain hole filling. It get better quality of depth sequence generated by sensor. This method is capable to produce high feature depth video which can be quite useful in improving the performance of various applications of Microsoft Kinect such as obstacle detection and avoidance, facial tracking, gesture recognition, pose estimation and skeletal. For stereo matching approach images depth extraction is the hybrid (Combination of Morphological Operation) mathematical algorithm. There are few step like color conversion, block matching, guided filtering, minimum disparity assignment design, mathematical perimeter, zero depth assignment, combination of hole filling and permutation of morphological operator and last nonlinear spatial filtering. Our algorithm is produce smooth, reliable, noise less and efficient depth map. The evaluation parameter such as Structure Similarity Index Map (SSIM), Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) measure the results for proportional analysis.en_US
dc.description.sponsorshipCollege of Agricultural Engineering and Technology, Junagadh Agricultural Universityen_US
dc.language.isoenen_US
dc.publisherOriental Journal of Computer Science and Technologyen_US
dc.subjectDepthen_US
dc.subjectDisparityen_US
dc.subjectGuided Filteren_US
dc.subjectKinecten_US
dc.subjectMorphological Filteren_US
dc.subjectStereo Matchingen_US
dc.subjectWarpen_US
dc.subjectZero Depthen_US
dc.subject3-Dimensionen_US
dc.titleReal Time Depth Hole Filling using Kinect Sensor and Depth Extract from Stereo Imagesen_US
dc.typeArticleen_US
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