• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.16 no.5
• /
• pp.134-140
• /
• 2017

Shape-from-shading (SFS) or stereo vision algorithms can be utilized to measure the shape of an object with imaging techniques for effective sensing in non-contact measurements. SFS algorithms could reconstruct the 3D information from a 2D image data, offering relatively comprehensive information. Meanwhile, a stereo vision algorithm needs several feature points or lines to extract 3D information from two 2D images. However, to measure the size of an object with a freeform surface, the two algorithms need some additional information, such as boundary conditions and grids, respectively. In this study, a stereo vision scheme using the depth information obtained by shape-from-shading as patterns was proposed to measure the size of an object with a freeform surface. The feasibility of the scheme was proved with an experiment where the images of an object were acquired by a CCD camera at two positions, then processed by SFS, and finally by stereo matching. The experimental results revealed that the proposed scheme could recognize the size and shape of freeform surface fairly well.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.12
• /
• pp.2503-2510
• /
• 2002

Since the first shape-form-shading technique was developed by Horn in the early 1970s, many different approaches have been continuously emerging in the past three decades. Some of them improve existing techniques, while others are completely new approaches. Using the image reflectance equation, they estimate the 3-D shape of an object utilizing adequate constraints. Each algorithm applies different constraints such as brightness, smoothness, and integrability to solve the shape-from-shading problem. Especially for symmetric objects, a symmetry constraint is proposed to improve the performance of existing shape-from-shading algorithm in this paper. The symmetry constraint is imposed to a conventional algorithm and then the improvement in the performance of 3-D shape reconstruction is proved by quantitatively comparing the depth and gradient errors.

• Journal of Computational Design and Engineering
• /
• v.3 no.2
• /
• pp.121-131
• /
• 2016

Organic modeling of 3D characters is a challenging task when it comes to correctly modeling the anatomy of the human body. Most sketch based modeling tools available today for modeling organic models (humans, animals, creatures etc) are focused towards modeling base mesh models only and provide little or no support to add details to the base mesh. We propose a hybrid approach which combines geometrical primitives such as generalized cylinders and cube with Shape-from-Shading (SFS) algorithms to create plausible human character models from sketches. The results show that an artist can quickly create detailed character models from sketches by using this hybrid approach.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.6
• /
• pp.73-81
• /
• 1996

In this paper, based on the constrained optimizatin technique and direct recovery method, we proesent a shape form shading (SFS) algorithm to recover a 3-D shape form an image. More specifically, we first employ the membrane model for a smoothness constraint to revoer a 3-D shape coarsely. We then compute the surface height directly to reduce the shape distortion due to a regularization term. In our approach, we can obtain a stable and accurate solution by the application of these two steps. Several simulation results on various images are provided and discussed in this paper and they show that the proposed algorithm extracts the 3-D information accurately and efficiently.