Deriving shape information from occluding contours in shape-from-shading problems

1992 ◽  
Author(s):  
Alexander M. Bonch-Osmolovsky
Author(s):  
Sanjay Bakshi ◽  
Yee-Hong Yang

Due to the complexity of the shape-from-shading problem, most solutions rely on idealistic conditions. Orthographic imaging, a known distant point light source, and known surface reflectance properties are usually assumed. Furthermore, most real surfaces are neither perfectly diffuse (Lambertian) nor ideally specular (mirror-like); however most shape-from-shading algorithms assume Lambertian reflectance. The behavior of shape-from-shading algorithms that rely on idealistic conditions is unpredictable in real imaging situations. In this paper, the LIRAS (LIght, Reflectance, And Shape) Recovery System is proposed. LIRAS is a practical approach to the shape-from-shading problem, as many of these assumptions are relaxed. LIRAS is also a modular system: there is a component that recovers the surface reflectance properties, thus the assumption of Lambertian reflectance is relaxed. Rather than assume a known illuminant direction, a component exists that can recover the light orientation. Once the reflectance map is determined, another LIRAS module can use this information to recover the shape for non-Lambertian surfaces. Each of these modules is described and a discussion of how the components cooperate to recover three-dimensional shape information in real environments is given. Extensive experimental evaluation is conducted using both synthetic and real images and the results are very encouraging. The contributions of this paper include the design and implementation of LIRAS and the extensive quantative and qualitative experimental results, which can provide guidelines for future refinements of other shape recovery systems.


1989 ◽  
Vol 1 (2) ◽  
pp. 208-217 ◽  
Author(s):  
Alex Pentland

A simple neural mechanism that recovers surface shape from image shading is derived from a simplified model of the physics of image formation. The mechanism's performance is surprisingly good even when applied to complex natural images, and is even able to extract significant shape information from some line drawings.


Author(s):  
Sheng-Liang Kao ◽  
Chiou-Shann Fuh

In this paper, a linear algorithm3,4 is proposed to recover shape information from multiple images, each of them is taken under the environment that all of the object surfaces are illuminated by a known near point light source. In this method, an approximate range of the distance for the objects to the viewer (e.g. camera) is previously defined. Using this predefined value, the absolute depth map of the objects can be found out.


2010 ◽  
Vol 130 (5) ◽  
pp. 873-881 ◽  
Author(s):  
Yoshiyuki Sato ◽  
Junichi Narita ◽  
Yoichi Kageyama ◽  
Makoto Nishida

1996 ◽  
Vol 76 (1-2) ◽  
pp. 117-125 ◽  
Author(s):  
G. Keith Humphrey ◽  
Lawrence A. SymonS ◽  
Andrew M. Herbert ◽  
Melvyn A. Goodale
Keyword(s):  

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Christian Kapeller ◽  
Ernst Bodenstorfer

Abstract Battery technology is a key component in current electric vehicle applications and an important building block for upcoming smart grid technologies. The performance of batteries depends largely on quality control during their production process. Defects introduced in the production of electrodes can lead to degraded performance and, more importantly, to short circuits in final cells, which is highly safety-critical. In this paper, we propose an inspection system architecture that can detect defects, such as missing coating, agglomerates, and pinholes on coated electrodes. Our system is able to acquire valuable production quality control metrics, like surface roughness. By employing photometric stereo techniques, a shape from shading algorithm, our system surmounts difficulties that arise while optically inspecting the black to dark gray battery coating materials. We present in detail the acquisition concept of the proposed system architecture, and analyze its acquisition-, as well as, its surface reconstruction performance in experiments. We carry these out utilizing two different implementations that can operate at a production speed of up to 2000 mm/s at a resolution of 50 µm per pixel. In this work we aim to provide a system architecture that can provide a reliable contribution to ensuring optimal performance of produced battery cells.


Cognition ◽  
2021 ◽  
Vol 212 ◽  
pp. 104664
Author(s):  
Ayelet Sapir ◽  
Ronen Hershman ◽  
Avishai Henik

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