Object-image-based method to construct an unweighted quality map for phase extraction and phase unwrapping

Fang, Suping; Wang, Leijie; Yang, Pengcheng; Meng, Liang; Komori, Masaharu

doi:10.1364/ao.50.001482

Cited by 11 publications

(13 citation statements)

References 19 publications

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“…Each fringe of the sinusoidal patterns was identified by a binary sequence q n . Then we constructed a (10,5) shorten extended Hamming code with a minimum Hamming distance d H at 4, with which the q n were embedded into 2M frames of binary stripes. With a colorprojection technique, the sinusoidal fringe patterns and binary stripes were projected simultaneously using RGB.…”

Section: Discussionmentioning

confidence: 99%

“…Consider an example where the number of fringe patterns is 20, the shortest message length will be k 5. As the length of C n is even, we considered (6,5), (8,5), (10,5) and (12,5) binary linear block codes. The corresponding upper bounds on the minimum Hamming distances are 2, 2, 4, and 4.…”

Section: B Composite Fringe Patterns Projectionmentioning

confidence: 99%

“…The fringe identification sequences q n are 32 5 bit binary digits from 0 to 31, where q 1 0; 0; 0; 0; 0 and q 32 1; 1; 1; 1; 1. Then C n is obtained by encoding each corresponding q n through the (10,5) encoder. The figure below shows the fringe patterns projected in each frame.…”

Section: Experiments Verificationsmentioning

confidence: 99%

“…[1][2][3][4][5][6]. A typical FPP system consists of a digital projector, a CCD camera, and a computer.…”

Section: Introductionmentioning

confidence: 99%

“…However, when large depth discontinuities are observed, the wrong decision of unwrapping may be made regarding the addition or subtraction of 2π. In order to implement reliable and accurate unwrapping, intensive studies have been devoted, and various approaches have been developed, including the quality-guided methods [2][3][4][5], the temporal method [6][7][8][9][10], and color-projectionbased methods [11][12][13][14][15][16][17][18]. With quality-guided methods, every pixel on the phase maps is associated with a quality value measuring the smoothness of the pixel in contrast to its surrounding ones.…”

Section: Introductionmentioning

confidence: 99%

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Three-dimensional measurement of object surfaces with complex shape and color distribution based on projection of color fringe patterns

Chen

et al. 2013

Appl. Opt.

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A challenging issue associated with three-dimensional (3D) fringe patterns profilometry (FPP) is the unwrapping of phase maps resulting from color object surfaces. This paper proposes a new colorprojectionbased 3D FPP, making use of the three primary color channels [i.e., red, green, and blue (RGB)] associated with digital projectors. One channel (e.g., red) is used for projecting sinusoidal fringes required by phase shift profilometry (PSP); the other two channels are employed for generating binary stripe patterns. In order to achieve reliable phase unwrapping, each fringe of the sinusoidal patterns is identified by a unique binary sequence. These sequences are then encoded by a channel-encoding scheme used in the area of communication. The encoded sequences are embedded in the binary coding stripe images, which are projected together with the sinusoidal patterns. The three image patterns are reflected by the object surface and captured by an RGB 3-CCD camera. The reflected sinusoidal patterns are employed to yield a wrapped phase map, and the binary stripe patterns are used to retrieve the encoded sequences, which are then decoded to yield the original binary sequences for phase unwrapping. Compared with existing color-encoded algorithms, the proposed approach uses binary codes instead of fringe color to identify the fringes, which are less sensitive to the disturbances caused by object surface color and illumination noises. Furthermore, use of the channel-coding scheme provides extra resistance to the disturbances caused by object surface color and illumination noises. Experimental results are presented to confirm the effectiveness of the proposed technique. A challenging issue associated with three-dimensional (3D) fringe patterns profilometry (FPP) is the unwrapping of phase maps resulting from color object surfaces. This paper proposes a new colorprojection-based 3D FPP, making use of the three primary color channels [i.e., red, green, and blue (RGB)] associated with digital projectors. One channel (e.g., red) is used for projecting sinusoidal fringes required by phase shift profilometry (PSP); the other two channels are employed for generating binary stripe patterns. In order to achieve reliable phase unwrapping, each fringe of the sinusoidal patterns is identified by a unique binary sequence. These sequences are then encoded by a channel-encoding scheme used in the area of communication. The encoded sequences are embedded in the binary coding stripe images, which are projected together with the sinusoidal patterns. The three image patterns are reflected by the object surface and captured by an RGB 3-CCD camera. The reflected sinusoidal patterns are employed to yield a wrapped phase map, and the binary stripe patterns are used to retrieve the encoded sequences, which are then decoded to yield the original binary sequences for phase unwrapping. Compared with existing color-encoded algorithms, the proposed approach uses binary codes instead of fringe color to identify the fringes, which are less se...

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Section: Discussionmentioning

confidence: 99%

Section: B Composite Fringe Patterns Projectionmentioning

confidence: 99%

Section: Experiments Verificationsmentioning

confidence: 99%

“…[1][2][3][4][5][6]. A typical FPP system consists of a digital projector, a CCD camera, and a computer.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Three-dimensional measurement of object surfaces with complex shape and color distribution based on projection of color fringe patterns

Chen

et al. 2013

Appl. Opt.

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Valid measurement region segmentation method for the interferogram based on local fringe distribution features

Yang

Zhu

et al. 2023

Optics Communications

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An object image edge detection based quality-guided phase unwrapping approach for fast three-dimensional measurement

Chen

Song

et al. 2013

2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Abstract²A new approach for achieving fast and reliable unwrapping of complex phase maps is presented for phase shifted based three-dimensional (3D) Fringe pattern profilometry (FPP). As phase unwrapping errors are often caused by shadows on fringe patterns images and object surface discontinuities, we propose to identify both of them. An image of the object is acquired by averaging the fringe patterns reflected from the object surface, based on which shadow areas and the phase discontinuities are identified. When carrying out phase unwrapping, the shadow areas and the edge pixels will be isolated, and then the remaining areas are unwrapped by means of an efficient technique proposed below. All the remaining pixels are then unwrapped by an efficient technique proposed, by which, the computational efficiency can be significantly improved. As proven by the experiment results, the proposed approach is able to implement fast and reliable phase unwrapping. I. INTRODUCTIONFringe Pattern Profilometry (FPP) has been an active area of research due to its potential application in many noncontact 3D shape measurement scenarios [1-3]. A typical FPP system consists of a projector, a digital camera and a computer. In most applications, the digital projector generates a group of sinusoidal fringe patterns images which are projected onto the object surface to be measured [1]. The image patterns are distorted due to the height variance of surface shape which are captured by the camera. As the fringe patterns are sinusoidal, and the deformed patterns can be modeled as the result of phase modulation of the projected patterns. Consequently, the fringe patterns can be described by phase maps, and the 3D shape can be retrieved by analyzing the phase maps. However, the obtained phases are wrapped into the range ( , ] SS referred to wrapped phases. In order to obtain the 3D shapes, the true phases are required and must be recovered from the wrapped ones. Such a process is known as phase unwrapping which is a critical step in the FPP approaches.Many phase unwrapping algorithms have been proposed. Existing phase unwrapping algorithms can be classified into two categories: the temporal algorithms (such as gray-code method [2] and multi-frequency method [3]) and spatial algorithms including simple path-following method [6], branch-cut method [7], and quality-guided flood-fill (QGFF) method [14]. The temporal algorithms are able to accurately recover the true phases from complex wrapped phase maps. However they usually require extra fringe patterns and thus not suit for fast 3D acquisition. On the other hand, the spatial algorithms can be applied in the cases of less number of fringe patterns, but they have limited ability to unwrap phase maps with isolated regions and discontinuities.

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Object-image-based method to construct an unweighted quality map for phase extraction and phase unwrapping

Cited by 11 publications

References 19 publications

Three-dimensional measurement of object surfaces with complex shape and color distribution based on projection of color fringe patterns

Three-dimensional measurement of object surfaces with complex shape and color distribution based on projection of color fringe patterns

Valid measurement region segmentation method for the interferogram based on local fringe distribution features

An object image edge detection based quality-guided phase unwrapping approach for fast three-dimensional measurement

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