• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.4
• /
• pp.395-399
• /
• 2006

A method to recognize unpaved road region using a 3D depth measurement system is proposed for mobile robots. For autonomous maneuvering of mobile robots, recognition of obstacles or recognition of road region is the essential task. In this paper, the 3D depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Therefore, the problem falls into a texture identification problem. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of unpaved trail are included in this paper.

• Journal of the Optical Society of Korea
• /
• v.15 no.4
• /
• pp.335-339
• /
• 2011

Recently, we reported a single input channel joint transform correlator for the color pattern recognition which decomposes the input color image into three R, G, and B gray components and adds those components into a single gray image in the input plane. This technique has the merit of a single input channel instead of three input channels. However, we found this technique has some problems with discrimination impossibility in the case of a simple primary color pattern which results in the same gray level through the addition process. Thus, we propose a modified coding technique which selectively recombines the decomposed three R, G, and B gray components instead of the simple adding process. Simulated results show that the modified coding technique can accurately discriminate a variety of kinds of color images.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.31A no.6
• /
• pp.61-69
• /
• 1994

For distortion-invariant recognition of Korean characters, a holographic implementation of an optical associative memory system is proposed. The structure of the proposed system is a single-layer neural network employing interconneclion matrix, thresholding and feedback. To provide the interconnection matrix, we use two CGII's which are placed on intermcdiate plane of cascaded Vander Lugt corrclators to form an optical memory loop. The holographic correlator stores reference images in a hologram and retrives them in a coherently illuminated feedback loop. An input image which maybe noisy or incomplete, is applicd to the system and simultaneously correlated optically with all of the stord images. These correlations are throsholed and fed back to the input, where the strongest correlation reinforces the input image. The enhanced image passes arround the loop repeatedly, approaching the stored image more closely on each pass until the system stabilizes on the desired image. The computer simulation results show that the proposed Korean Character recognition algorithm has high discrimination capability and noise immunity.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.8
• /
• pp.848-855
• /
• 2008

In this paper, we describe correspondence among multiple images taken by multiple cameras. The correspondence among multiple views is an interesting problem which often appears in the application like visual surveillance or gesture recognition system. We use the principal axis and the ground plane homography to estimate foot of human. The principal axis belongs to the subtracted silhouette-based region of human using subtraction of the predetermined multiple background models with current image which includes moving person. For the calculation of the ground plane homography, we use landmarks on the ground plane in 3D space. Thus the ground plane homography means the relation of two common points in different views. In the normal human being, the foot of human has an exactly same position in the 3D space and we represent it to the intersection in this paper. The intersection occurs when the principal axis in an image crosses to the transformed ground plane from other image. However the positions of the intersection are different depend on camera views. Therefore we construct the correspondence that means the relationship between the intersection in current image and the transformed intersection from other image by homography. Those correspondences should confirm within a short distance measuring in the top viewed plane. Thus, we track a person by these corresponding points on the ground plane. Experimental result shows the accuracy of the proposed algorithm has almost 90% of detecting person for tracking based on correspondence of intersections.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.10
• /
• pp.2280-2286
• /
• 2012

In this paper, we propose a novel nonlinear 3D image correlator using a fast computational integral imaging reconstruction (CIIR) method. In order to implement the fast CIIR method, the magnification process was eliminated. In the proposed correlator, elemental images of the reference and target objects are picked up by lenslet arrays. Using these elemental images, reference and target plane images are reconstructed on the output plane by means of the proposed fast CIIR method. Then, through nonlinear cross-correlations between the reconstructed reference and the target plane images, the pattern recognition can be performed from the correlation outputs. Nonlinear correlation operation can improve the recognition of 3D objects. To show the feasibility of the proposed method, some preliminary experiments are carried out and the results are presented by comparing the conventional method.

• The Journal of Korea Robotics Society
• /
• v.4 no.3
• /
• pp.185-191
• /
• 2009

This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship betweenfeatures, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.4903-4929
• /
• 2018

In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.

• Journal of Korea Multimedia Society
• /
• v.14 no.2
• /
• pp.171-181
• /
• 2011

A vision-based method for positioning and orienting of pallets is presented in this paper, which guides autonomous forklifts to engage pallets automatically. The method uses a single camera mounted on the fork carriage instead of two cameras for stereo vision that is conventionally used for positioning objects in 3D space. An image back-projection technique for determining the orient of a pallet without any fiducial marks is suggested in tins paper, which projects two feature lines on the front plane of the pallet backward onto a virtual plane that can be rotated around a given axis in 3D space. We show the fact that the rotation angle of the virtual plane on which the back-projected feature lines are parallel can be used to describe the orient of the pallet front plane. The position of the pallet is determined by using ratio of the distance between the back-projected feature lines and their real distance on the pallet front plane. Through a test on real pallet images, we found that the proposed method was applicable to real environment practically in real-time.

• Proceedings of the KSME Conference
• /
• 2001.06a
• /
• pp.108-113
• /
• 2001

Recently, the mechanical structures applied to many industrial products, especially in electronic products, appear to be miniaturized and complicated. This trend makes it difficult to analyze the stress distribution of those mechanical structures and generates new challenges for precise measurement of strain. Therefore, generally most of those cases largely depend on the finite element analysis. But the development of optical metrology which has the capability of non-contact, full-field and precise measurement makes it possible to solve these measuring problems. Among the optical measurement techniques, the electronic speckle pattern interferometry (ESPI) has been developed and considered as one of the most useful tools for measuring displacement and deformation. But the shortage of recognition and difficulties of measurement have limited its industrial applications in spite of its excellent capabilities. Therefore in this study, in order to enhance the industrial application of ESPI, the measurement of in-plane displacement of mechanical structure with ESPI, which is applied to washing machine and cannot be measured by strain gauges, was performed. And the verification of validity of FEA results was also done.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.4
• /
• pp.693-700
• /
• 2002

Recently, the mechanical structures applied to many industrial products, especially in electronic products, appear to be miniaturized and complicated. This trend makes it difficult to analyze the stress distribution of those mechanical structures and generates new challenges for precise measurement of strain. In order to solve this measurement problem many optical measurement techniques have been suggested. Among those, the ESPI(Electronic Speckle Pattern Interferometry) has been considered as one of the most useful tools. But the shortage of recognition and difficulties of measurement have limited its industrial applications in spite of its excellent capabilities. Therefore in this study, not only the verification of the FEA result but the enhancement of industrial application of ESPI was tried by measuring the in-plane displacement of mechanical structure with ESPI, which is difficult to be measured with strain gauge.