Computer-generated holograms of three-dimensional realistic objects recorded without wave interference

We propose a method of synthesizing computer-generated holograms of real-life three-dimensional (3-D) objects. An ordinary digital camera illuminated by incoherent white light records several projections of the 3-D object from different points of view. The recorded data are numerically processed to yield a two-dimensional complex function, which is then encoded as a computer-generated hologram. When this hologram is illuminated by a plane wave, a 3-D real image of the object is reconstructed.     

Distortion-tolerant three-dimensional object recognition with digital holography

We present a technique to implement three-dimensional (3-D) object recognition based on phase-shift digital holography. We use a nonlinear composite correlation filter to achieve distortion tolerance. We take advantage of the properties of holograms to make the composite filter by using one single hologram. Experiments are presented to illustrate the recognition of a 3-D object in the presence of out-of-plane rotation and longitudinal shift along the z axis.     

Optical image recognition of three-dimensional objects

A three-dimensional (3-D) optical image-recognition technique is proposed and studied. The proposed technique is based on two-pupil optical heterodyne scanning and is capable of performing 3-D image recognition. A hologram of the 3-D reference object is first created and then is used to modulate spatially one of the pupils of the optical system; the other pupil is a point source. A 3-D target object to be recognized is then scanned in two dimensions by optical beams modulated by the two pupils. The result of the two-dimensional scan pattern effectively displays the correlation of the holographic information of the 3-D reference object and that of the 3-D target object. A strong correlation peak results if the two pieces of the holographic information are matched. We analyze the proposed technique and thereby lay a theoretical foundation for optical implementations of the idea. Finally, computer simulations are performed to verify the proposed idea.     

Recognition and classification of three-dimensional phase objects by digital Fresnel holography

We demonstrate the validity of wavelet-based processing for recognition and classification of three-dimensional phase objects. One Fresnel digital hologram of each of the three-dimensional (3-D) phase objects to be classified is recorded. The electronic holograms are processed digitally to permit 3-D object information to be retrieved as two-dimensional digital complex images. We use a Mexican-hat wavelet- matched filter (WMF) to enhance the correlation peak and discriminate between the objects. The WMF performs a wavelet transform (WT) to enhance the significant features of the images and the correlation of the WT coefficients thus obtained. We compare the feasibility of a WMF-based object classifier with the matched-filter-based classifier to classify our four 3-D phase objects in a 3-D scene into true or false classes with minimal error.     

Generation of three-dimensional integral images from a holographic pattern of 3-D objects

We present a novel approach for generating three-dimensional (3-D) integral images from a fringe pattern of 3-D objects. A recorded hologram of 3-D objects is segmented into a number of subholograms. Then, different views of 3-D objects are reconstructed from them because each subhologram has its own perspective of 3-D objects in the recording process. These locally reconstructed images can be rearranged as the same subimage array of the conventional integral-imaging system and transformed into virtually picked-up elemental images of 3-D objects. From this newly generated elemental image array, 3-D images could easily be reconstructed by using a white light. Experiments with a 3-D test object have been performed and the results have been presented.     

Scale-invariant recognition of three-dimensional objects by use of a quasi-correlator

A method of scale-invariant recognition of three-dimensional (3-D) objects is presented. Several images of the observed scene are recorded under white-light illumination from several different points of view and compressed into a single complex two-dimensional matrix. After filtering with a single scale-invariant filter, the resultant function is then coded into a computer-generated hologram (CGH). When this CGH is coherently illuminated, a correlation space is reconstructed in which light peaks indicate the existence and location of true targets in the tested 3-D scene. The light peaks are detectable for different sizes of the true objects, as long as they are within the invariance range of the filter. Experimental results in a complete electro-optical system are presented, and comparisons with other systems are investigated by use of computer simulation.     

Three-dimensional pattern recognition with a single two-dimensional synthetic reference function

A novel, to our knowledge, method of distortion-invariant three-dimensional (3-D) pattern recognition is proposed. A single two-dimensional synthetic discriminant function is employed as a reference function in the 3-D correlator. Thus the proposed system is able to identify and locate any true-class object in the 3-D scene. Preliminary simulation and experimental results are presented.     

Recurrence formulas for fast creation of synthetic three-dimensional holograms

A method for accelerating the synthesis of computer-generated three-dimensional (3-D) holograms, based on conventional ray tracing, is proposed. In ray tracing, computers expend almost all of their resources in calculating the 3-D distances between each one of the point sources composing an object and a sampling point on the hologram. We present recurrence formulas that precisely compute the distances and reduce the computation time for synthesizing holograms to one half to one quarter, depending on the processor type. We demonstrate that a full-parallax hologram with an area of 4800 x 4800 pixels, synthesized for a 3-D object containing 966 point sources of light, is computed within 17 min and is optically reconstructed.     

Three-dimensional matching by use of phase-only holographic information and the Wigner distribution

Matching of three-dimensional (3-D) objects is achieved by Wigner analysis of the correlation pattern between the phase-only holographic information of a reference object and that of a target object. First, holographic information on the reference object and on the target object is extracted by use of optical scanning holography as a form of electrical signal. This electrical information is then stored in a computer for digital processing. In the digital computer, the correlation between the phase-only information of the hologram of the reference object and that of the target object is calculated and analyzed by use of a Wigner distribution. The Wigner distribution yields a space-frequency map of the correlation pattern that indicates whether the 3-D image of the target object matches that of the reference object. When the 3-D image of the target object matches that of the reference object, the Wigner distribution gives a well-defined line that directly indicates the 3-D location of the matched target object. Optical experiments with digital processing are described to demonstrate the proposed matching technique.     

Two-channel self-focusing matched filter

Abstract

A two-channel self-focusing matched filter produced by a computer generated hologram is proposed in this paper. The filter function is synthesized for two different objects to be recognized. The composite filter function consists of two terms, one of which is formed by adding a negative quadratic phase factor into the conjugate Fourier spectrum of one object, and another, which is adding a positive quadratic phase factor into the Fourier spectrum of another object. The composite function is then encoded into a computer-generated hologram to fabricate a matched filter. When performing pattern recognition, the filter will produce two correlation signals of two objects in the first positive order and the first negative order of diffraction, respectively. The diffracted light can be self-focused in the plane at a designed distance behind the filter. The optical experiments have shown the capability of the filter for simultaneously recognizing two different objects.     

Binary representation of interference patterns for phase-shifting digital hologram

Phase-shifting digital holograms can completely record the complex (amplitude and phase) wavefront information, containing three-dimensional object shape and relative position. In this study, we examine a binary representation for a phase-shifting digital hologram and apply it to three-dimensional object recognition and reconstruction. For this purpose, we derive an optimal threshold and quantized value for the binary representation of the interference patterns. The recognition results indicate that even with only one bit to represent the digital hologram, there is still enough information for us to recognize the three-dimensional objects. By using the proposed algorithms, one can easily implement the overall recognition process in real-time applications.     

Optical pattern recognition using a unidirectional photorefractive oscillator coupled with an angular multiplexing volume hologram

Abstract

We propose and demonstrate a unidirectional photorefractive ring oscillator that couples with an external angular multiplexing volume hologram for pattern recognition. By configuring the hologram externally, a computer-generated hologram (CGH) and a spatial light modulator are utilized to generate reference beams for the hologram. Two-dimensional images are stored in the form of resonating beams in the system, whereby the nonlinear interaction between the beams allows the image that most resembles an input object to be recognized. Five images were used to illustrate the pattern recognition ability of the oscillator. It was found that the input object was successfully recognized within 10s. The fact that CGHs can generate a large number of beamlets enhances significantly the storage capacity in this system.     

Single beam two-views holographic particle image velocimetry

Holographic particle image velocimetry (HPIV) is presently the only method that can measure at high resolution all three components of the velocity in a finite volume. In systems that are based on recording one hologram, velocity components parallel to the hologram can be measured throughout the sample volume, but elongation of the particle traces in the depth direction severely limits the accuracy of the velocity component that is perpendicular to the hologram. Previous studies overcame this limitation by simultaneously recording two orthogonal holograms, which inherently required four windows and two recording systems. This paper introduces a technique that maintains the advantages of recording two orthogonal views, but requires only one window and one recording system. Furthermore, it enables a quadruple increase in the spatial resolution. This method is based on placing a mirror in the test section that reflects the object beam at an angle of 45 degrees. Particles located in the volume in which the incident and reflected beams from the mirror overlap are illuminated twice in perpendicular directions. Both views are recorded on the same hologram. Off-axis holography with conjugate reconstruction and high-pass filtering is used for recording and analyzing the holograms. Calibration tests show that two views reduce the uncertainty in the three-dimensional (3-D) coordinates of the particle centroids to within a few microns. The velocity is still determined plane-by-plane by use of two-dimensional particle image velocimetry procedures, but the images are filtered to trim the elongated traces based on the 3-D location of the particle. Consequently, the spatial resolution is quadrupled. Sample data containing more than 200 particles/mm3 are used for calculating the 3-D velocity distributions with interrogation volumes of 220 x 154 x 250 microm, and vector spacing of 110 x 77 x 250 microm. Uncertainty in velocity is addressed by examining how well the data satisfies the continuity equation. The results show significant improvements compared with previous procedures. Limitations of the technique are also discussed.     

Hybrid holographic microscopy: visualization of three-dimensional object information by use of viewing angles

One of the attractive features of hybrid holographic microscopy, in which the hologram of a microscopic object recorded by an image sensor is numerically reconstructed with a computer, is that the three-dimensional (3-D) information of a recorded object is obtained. The 3-D information has often been extracted by means of changing the reconstruction distance in the numerical reconstruction process, but here we describe an alternative technique that allows for variable viewing angles. That is, the perspective from which the object is viewed can be varied. The approximation used enables use of the fast-Fourier-transform algorithm for numerical reconstruction even in the high-resolution case in which the Fresnel approximation is no longer valid. The resolution of the proposed technique is also discussed.     

Modified Fresnel computer-generated hologram directly recorded by multiple-viewpoint projections

An efficient method for obtaining modified Fresnel holograms of real existing three-dimensional (3-D) scenes illuminated by incoherent white light is presented. To calculate the hologram, the method uses multiple-viewpoint projections of the 3-D scene. However, contrary to other similar methods, this one is able to calculate the Fresnel hologram of the 3-D scene directly rather than calculating a Fourier hologram first. This significantly decreases the amount of calculations needed to obtain the hologram and also reduces the reconstruction errors. The proposed method is first mathematically introduced and then demonstrated by both simulations and experiments.     

Effective reduction of the novel look-up table memory size based on a relationship between the pixel pitch and reconstruction distance of a computer-generated hologram

In this paper, we propose an approach, new to our knowledge, to effectively generate and reconstruct the resolution-enhanced computer-generated hologram (CGH) of three-dimensional (3-D) objects with a significantly reduced in memory size novel look-up table (N-LUT) by taking into account a relationship between the pixel pitch and reconstruction distance of the hologram pattern. In the proposed method, a CGH pattern composed of shifted versions of the principal fringe patterns (PFPs) with a short pixel pitch can be reconstructed just by using the CGH generated with a much longer pixel pitch by controlling the hologram reconstruction distance. Accordingly, the corresponding N-LUT memory size required for resolution-enhanced hologram patterns can be significantly reduced in the proposed method. To confirm the feasibility of the proposed method, experiments are carried out and the results are discussed.     

Compression of digital holograms for three-dimensional object reconstruction and recognition

We present the results of applying lossless and lossy data compression to a three-dimensional object reconstruction and recognition technique based on phase-shift digital holography. We find that the best lossless (Lempel-Ziv, Lempel-Ziv-Welch, Huffman, Burrows-Wheeler) compression rates can be expected when the digital hologram is stored in an intermediate coding of separate data streams for real and imaginary components. The lossy techniques are based on subsampling, quantization, and discrete Fourier transformation. For various degrees of speckle reduction, we quantify the number of Fourier coefficients that can be removed from the hologram domain, and the lowest level of quantization achievable, without incurring significant loss in correlation performance or significant error in the reconstructed object domain.     

基于结构照明和BP神经网络的三维物体识别

提出一种具有旋转不变性的三维物体识别的新方法,该方法通过结构光照明的方法,使物体的高度分布以变形条纹的形式编码于二维强度图中,由于条纹图包含有物体的高度分布信息,因此对条纹的相关识别具有本征三维识别的特点.旋转不变性是通过BP神经网络实现的.计算机模拟结果表明,用二维强度像的基频分量做训练样本设计BP神经网络,选择训练样本和隐藏层神经元的数目,基于结构光编码的BP神经网络对三维物体具有良好的旋转不变识别效果.     

Three-dimensional object recognition by fourier transform profilometry

An automatic method for three-dimensional (3-D) shape recognition is proposed. It combines the Fourier transform profilometry technique with a real-time recognition setup such as the joint transform correlator (JTC). A grating is projected onto the object surface resulting in a distorted grating pattern. Since this pattern carries information about the depth and the shape of the object, their comparison provides a method for recognizing 3-D objects in real time. A two-cycle JTC is used for this purpose. Experimental results demonstrate the theory and show the utility of the new proposed method.