Location of polyhedral objects in 3-D space from three unconstrained edge points

In order to resist print and scan attacks, a kind of digital halftone image watermarking algorithm is proposed, which is based on the edge detection and improved error diffusion. The edge of gray image is gotten using canny detection. Calculate the noise visibility function values of the edge points. Then, sort the values in ascending order and select the size that equal to the length of watermark as the location of watermark embedding. While the grayscale image turns to halftone image using the improved error diffusion algorithm, binary watermark is embedded in the edge position. Watermark is pretreated with Arnold before embedding to improve the safety of watermark. Experiment results show that the algorithm is good resistance to print and scan attacks, while resistance to shearing, noise and jpeg compression attacks.

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Vision for mobile robots

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.1992.0112 ◽

1992 ◽

Vol 337 (1281) ◽

pp. 341-350 ◽

Cited By ~ 15

Keyword(s):

Mobile Robot ◽

Mobile Robots ◽

Structure From Motion ◽

Optic Flow ◽

Image Sequences ◽

Additional Constraint ◽

Feature Points ◽

Scene Structure ◽

Corner Points ◽

Edge Points

Localized feature points, particularly corners, can be computed rapidly and reliably in images, and they are stable over image sequences. Corner points provide more constraint than edge points, and this additional constraint can be propagated effectively from corners along edges. Implemented algorithms are described to compute optic flow and to determine scene structure for a mobile robot using stereo or structure from motion. It is argued that a mobile robot may not need to compute depth explicitly in order to navigate effectively.

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Analisis Algoritma Shi-Tomasi Dalam Pengujian Citra Senyum Pada Wajah Manusia

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) ◽

10.29207/resti.v5i6.3496 ◽

2021 ◽

Vol 5 (6) ◽

pp. 1036-1043

Author(s):

Ardi wijaya ◽

Puji Rahayu ◽

Rozali Toyib

Keyword(s):

Image Processing ◽

Corner Point ◽

Confusion Matrix ◽

Target Image ◽

Edge Points ◽

Ballistic Test ◽

Image Processing Algorithms ◽

Processing Algorithms ◽

Facial Images ◽

Angle Calculation

Problems in image processing to obtain the best smile are strongly influenced by the quality, background, position, and lighting, so it is very necessary to have an analysis by utilizing existing image processing algorithms to get a system that can make the best smile selection, then the Shi-Tomasi Algorithm is used. the algorithm that is commonly used to detect the corners of the smile region in facial images. The Shi-Tomasi angle calculation processes the image effectively from a target image in the edge detection ballistic test, then a corner point check is carried out on the estimation of translational parameters with a recreation test on the translational component to identify the cause of damage to the image, it is necessary to find the edge points to identify objects with remove noise in the image. The results of the test with the shi-Tomasi algorithm were used to detect a good smile from 20 samples of human facial images with each sample having 5 different smile images, with test data totaling 100 smile images, the success of the Shi-Tomasi Algorithm in detecting a good smile reached an accuracy value of 95% using the Confusion Matrix, Precision, Recall and Accuracy Methods.

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Formation of Geometric Tolerance Zones for Polyhedral Objects

Volume 2: 23rd Design Automation Conference ◽

10.1115/detc97/dac-3990 ◽

1997 ◽

Author(s):

Utpal Roy ◽

Bing Li

Keyword(s):

Variational Model ◽

Tolerance Zone ◽

Geometric Tolerance ◽

Geometric Tolerances ◽

Polyhedral Objects ◽

Different Types ◽

Tolerance Zones ◽

Algebraic Constraints ◽

Size Tolerance ◽

Part Model

Abstract This paper presents a scheme for establishing geometric tolerance zones for polyhedral objects in solid modelers. The proposed scheme is based on a surface-based variational model. Variations are applied to a part model by varying each surface’s model variables. Those model variables are constrained by some algebraic relations derived from the specified geometric tolerances. For size tolerance, two types of tolerance zones are considered in order to reflect two different types of size tolerances. For any other geometric tolerance (form, orientation or positional), the resultant tolerance zone is defined by the combination of size tolerance and that particular geometric tolerance specifications. Appropriate algebraic constraints (on the model variables) are finally used to establish the tolerance zone boundaries in the surface-based variational model.

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