3D Image Correlator using Computational Integral Imaging Reconstruction Based on Modified Convolution Property of Periodic Functions

被引:7
作者
Jang, Jae-Young [1 ]
Shin, Donghak [2 ]
Lee, Byung-Gook [2 ]
Hong, Suk-Pyo [3 ]
Kim, Eun-Soo [3 ]
机构
[1] Dongseo Univ, iReal Co, Pusan 617716, South Korea
[2] Dongseo Univ, Inst Ambient Intelligence, Pusan 617716, South Korea
[3] Kwangwoon Univ, HoloDigilog Human Media Res Ctr HoloDigilog, Seoul 139701, South Korea
基金
新加坡国家研究基金会;
关键词
Integral imaging; 3D correlation; Elemental images; Lenslet array; OCCLUDED OBJECTS; PICKUP METHOD; VISUALIZATION; DISPLAY;
D O I
10.3807/JOSK.2014.18.4.388
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.
引用
收藏
页码:388 / 394
页数:7
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