scholarly journals Deteksi Tungkai Bayi Pada Image Sequence Berbasis Vector Depth Estimation

2021 ◽  
Vol 7 (3) ◽  
pp. 35-42
Author(s):  
Faisal Lutfi Afriansyah ◽  
Niyalatul Muna
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
3D Reconstruction ◽  
Reference Frame ◽  
Fundamental Matrix ◽  
Motion Vector ◽  
Depth Estimation ◽  
Image Sequence ◽  
Image Sequences ◽  
The Right

Image processing in the image sequence for pattern recognition can be a solution for detecting limb movements in infants after surgery, but the camera is not calibrated. So we need the right method solution to be able to detect these conditions. This happens to cameras that are generally not calibrated and do not have the feature to calculate the vector depth for 3D reconstruction. Because to detect and find limb movement depth is needed to be able to do 3D reconstruction, because it is not only based on the x and y parameters but also z so that with the additional parameters it makes it easier to analyze the motion of the motion axis and the motion vector. This paper discusses a method for detecting 2D motion into a 3D-based motion vector by sequencing the image sequence image then finding the point of transfer of the motion frame destination from the frame reference frame by obtaining the depth (depth vector) using the fundamental matrix from the generated motion vector. This method is recommended because it can perform 3D reconstruction from input in the form of 2D image sequences by calculating the intrinsic parameters so that 3D reconstruction can be carried out. So that the limb vector movement in infants that was originally 2D can be reconstructed into 3D based and makes it easier to carry out the analysis because of the additional parameters.

scholarly journals CLASSIFICATION OF FEATURES OF IMAGE SEQUENCES

2015 ◽  
Vol XL-5/W6 ◽  
pp. 79-81 ◽  
Author(s):  
E. V. Pugin ◽  
A. L. Zhiznyakov
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Feature Space ◽  
Image Sequence ◽  
Image Sequences ◽  
Semantic Features ◽  
Single Image ◽  
Video Cameras

Processing of image sequences is a very actual trend now. This is confirmed with a vast amount of researches in that area. The possibility of an image sequence processing and pattern recognition became available because of increased computer capabilities and better photo and video cameras. The feature extraction is one of the main steps during image processing and pattern recognition. This paper presents a novel classification of features of image sequences. The proposed classification has three groups: 1) features of a single image, 2) features of an image sequence, 3) semantic features of an observed scene. The first group includes features extracted from a single image. The second group consists of features of any kinds of image sequences. The third group contains semantic features. Reverse feature clarification method is the iterative method when on each iteration we use higher level features to extract lower level features more precisely. The proposed classification of features of image sequences solves a problem of decomposition of the source feature space into several groups. Reverse feature clarification method allows to increase the quality of image processing during iterative process.

scholarly journals The determination of high-resolution spatio-temporal glacier motion fields from time-lapse sequences

2017 ◽  
Vol 5 (4) ◽  
pp. 861-879 ◽  
Author(s):  
Ellen Schwalbe ◽  
Hans-Gerd Maas
Keyword(s):  
High Resolution ◽  
Vector Fields ◽  
Motion Vector ◽  
Image Sequence ◽  
Image Sequences ◽  
Glacier Surface ◽  
Sequence Processing ◽  
Image Sequence Processing ◽  
Matching Techniques

Abstract. This paper presents a comprehensive method for the determination of glacier surface motion vector fields at high spatial and temporal resolution. These vector fields can be derived from monocular terrestrial camera image sequences and are a valuable data source for glaciological analysis of the motion behaviour of glaciers. The measurement concepts for the acquisition of image sequences are presented, and an automated monoscopic image sequence processing chain is developed. Motion vector fields can be derived with high precision by applying automatic subpixel-accuracy image matching techniques on grey value patterns in the image sequences. Well-established matching techniques have been adapted to the special characteristics of the glacier data in order to achieve high reliability in automatic image sequence processing, including the handling of moving shadows as well as motion effects induced by small instabilities in the camera set-up. Suitable geo-referencing techniques were developed to transform image measurements into a reference coordinate system.The result of monoscopic image sequence analysis is a dense raster of glacier surface point trajectories for each image sequence. Each translation vector component in these trajectories can be determined with an accuracy of a few centimetres for points at a distance of several kilometres from the camera. Extensive practical validation experiments have shown that motion vector and trajectory fields derived from monocular image sequences can be used for the determination of high-resolution velocity fields of glaciers, including the analysis of tidal effects on glacier movement, the investigation of a glacier's motion behaviour during calving events, the determination of the position and migration of the grounding line and the detection of subglacial channels during glacier lake outburst floods.

scholarly journals Determination of high resolution spatio-temporal glacier motion fields from time-lapse sequences

2017 ◽  
Author(s):  
Ellen Schwalbe ◽  
Hans-Gerd Maas
Keyword(s):  
High Resolution ◽  
Vector Fields ◽  
High Reliability ◽  
Motion Vector ◽  
Image Sequence ◽  
Image Sequences ◽  
Sequence Processing ◽  
Image Sequence Processing ◽  
Matching Techniques

Abstract. This paper presents a comprehensive method for the determination of motion vector fields of glaciers at high spatial and temporal resolution. These vector fields can be derived from monocular terrestrial camera image sequences and are a valuable data source for glaciological analysis of the motion behaviour of glaciers. The measurement concepts for the acquisition of image sequences are presented, and an automated monoscopic image sequence processing chain is developed. Motion vector fields can be derived with high precision by applying automatic sub-pixel-accuracy image matching techniques on grey value patterns in the image sequences. Well-established matching techniques have been adapted to the special characteristics of the glacier data in order to achieve high reliability in automatic image sequence processing, including the handling of moving shadows as well as motion effects induced by small instabilities in the camera setup. Suitable geo-referencing techniques were developed to transform image measurements into a reference coordinate system. The result of the monoscopic image sequence analysis is a dense raster of glacier surface point trajectories for each image sequence. Each translation vector component in these trajectories can be determined with an accuracy of some centimetres for points at a distance of several kilometres from the camera. Extensive practical validation experiments show that motion vector and trajectory fields derived from monocular image sequences can be used for the determination of high resolution velocity fields of glaciers, for the analysis of the effects of tides on glacier movement, for the investigation of a glacier's motion behaviour during calving events, for the determination of the position and migration of the grounding line and for the detection of sub glacial channels during glacier lake outburst floods.

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

A μc-Si:H P-I-N Imager For 2-D Pattern Recognition

1999 ◽  
Vol 558 ◽  
Author(s):  
J. Martins ◽  
M. Fernandes ◽  
F. Sousa ◽  
P. Louro ◽  
A. MaçArico ◽  
...  
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Image Enhancement ◽  
Image Representation ◽  
Rectangular Grid ◽  
Sensing Element ◽  
Coplanar Electrodes ◽  
Basic Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms

ABSTRACTA TCO/ μc-p-i-n Si:H/AI imager is presented and analyzed. The μc-p-i-n Si:H photodiode acts as a sensing element. Contacts are used as an electrical interface. The image is acquired by a scan-out process. Sampling is performed on a rectangular grid, and the read-out of the photogenerated charges is achieved by measuring simultaneously both transverse photovoltages at the coplanar electrodes. The image representation in gray-tones is obtained by using low level processing algorithms. Basic image processing algorithms are developed for image enhancement and restoration.

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