scholarly journals Cutting Affine Moment Invariants

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Jianwei Yang ◽  
Ming Li ◽  
Zirun Chen ◽  
Yunjie Chen
Keyword(s):  
Image Processing ◽  
Closed Curve ◽  
Experimental Results ◽  
Moment Invariants ◽  
Affine Invariant ◽  
Original Image ◽  
Invariant Features ◽  
General Contour ◽  
Classification Tasks ◽  
Affine Moment Invariants

The extraction of affine invariant features plays an important role in many fields of image processing. In this paper, the original image is transformed into new images to extract more affine invariant features. To construct new images, the original image is cut in two areas by a closed curve, which is called general contour (GC). GC is obtained by performing projections along lines with different polar angles. New image is obtained by changing gray value of pixels in inside area. The traditional affine moment invariants (AMIs) method is applied to the new image. Consequently, cutting affine moment invariants (CAMIs) are derived. Several experiments have been conducted to evaluate the proposed method. Experimental results show that CAMIs can be used in object classification tasks.

scholarly journals Extraction of Affine Invariant Features Using Fractal

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jianwei Yang ◽  
Guosheng Cheng ◽  
Ming Li
Keyword(s):  
Pattern Recognition ◽  
Feature Vector ◽  
Fractal Dimensions ◽  
Input Pattern ◽  
Experimental Results ◽  
Central Projection ◽  
Affine Invariant ◽  
Invariant Features ◽  
General Contour ◽  
New Feature

An approach based on fractal is presented for extracting affine invariant features. Central projection transformation is employed to reduce the dimensionality of the original input pattern, and general contour (GC) of the pattern is derived. Affine invariant features cannot be extracted from GC directly due to shearing. To address this problem, a group of curves (which are called shift curves) are constructed from the obtained GC. Fractal dimensions of these curves can readily be computed and constitute a new feature vector for the original pattern. The derived feature vector is used in question for pattern recognition. Several experiments have been conducted to evaluate the performance of the proposed method. Experimental results show that the proposed method can be used for object classification.

THE MELLIN CENTRAL PROJECTION TRANSFORM

2017 ◽  
Vol 58 (3-4) ◽  
pp. 256-264
Author(s):  
JIANWEI YANG ◽  
LIANG ZHANG ◽  
ZHENGDA LU
Keyword(s):  
Radial Direction ◽  
Mellin Transform ◽  
Closed Curve ◽  
Chinese Characters ◽  
Central Projection ◽  
Affine Invariant ◽  
Closed Curves ◽  
Affine Invariants ◽  
Invariant Features ◽  
Special Case

The central projection transform can be employed to extract invariant features by combining contour-based and region-based methods. However, the central projection transform only considers the accumulation of the pixels along the radial direction. Consequently, information along the radial direction is inevitably lost. In this paper, we propose the Mellin central projection transform to extract affine invariant features. The radial factor introduced by the Mellin transform, makes up for the loss of information along the radial direction by the central projection transform. The Mellin central projection transform can convert any object into a closed curve as a central projection transform, so the central projection transform is only a special case of the Mellin central projection transform. We prove that closed curves extracted from the original image and the affine transformed image by the Mellin central projection transform satisfy the same affine transform relationship. A method is provided for the extraction of affine invariants by employing the area of closed curves derived by the Mellin central projection transform. Experiments have been conducted on some printed Chinese characters and the results establish the invariance and robustness of the extracted features.

scholarly journals Robust Affine Invariant Descriptors

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Jianwei Yang ◽  
Zirun Chen ◽  
Wen-Sheng Chen ◽  
Yunjie Chen
Keyword(s):  
Additive Noise ◽  
Experimental Results ◽  
Affine Invariant ◽  
General Contour ◽  
Robust To Noise ◽  
Gray Values

An approach is developed for the extraction of affine invariant descriptors by cutting object into slices. Gray values associated with every pixel in each slice are summed up to construct affine invariant descriptors. As a result, these descriptors are very robust to additive noise. In order to establish slices of correspondence between an object and its affine transformed version, general contour (GC) of the object is constructed by performing projection along lines with different polar angles. Consequently, affine in-variant division curves are derived. A slice is formed by points fall in the region enclosed by two adjacent division curves. To test and evaluate the proposed method, several experiments have been conducted. Experimental results show that the proposed method is very robust to noise.

RADIAL CENTROID CURVE FOR AFFINE INVARIANT FEATURES EXTRACTION

2012 ◽  
Vol 10 (04) ◽  
pp. 1250035 ◽  
Author(s):  
JIANWEI YANG ◽  
RUSHI LAN ◽  
YUAN YAN TANG ◽  
YUNJIE CHEN
Keyword(s):  
Computer Vision ◽  
Wavelet Transform ◽  
Line Segment ◽  
Invariant Function ◽  
Closed Curve ◽  
Affine Invariant ◽  
Stationary Wavelet Transform ◽  
Radial Line ◽  
Invariant Features ◽  
Wavelet Methods

The extraction of affine invariant features plays an important role in many fields of computer vision. Contour-based wavelet methods are unapplicable to objects with several separable components. In this paper, a method is proposed by converting the object into a closed curve, which is called radial centroid curve (RCC). Point on this curve is the centroid of radial line segment from centroid of the object. It is shown that the RCC derived from the affine transformed object is the same affine transformed version as that of the original object. An affine invariant function (AIF) is constructed by applying stationary wavelet transform (SWT) to the derived RCC. This scheme is applicable to objects with several separable components. Several experiments have been conducted to evaluate the performance of the proposed method.

Method on 3D Dense Point Cloud Recovery of Geographical Scene

2013 ◽  
Vol 748 ◽  
pp. 619-623 ◽  
Author(s):  
Yan Liang ◽  
Ye Hua Sheng ◽  
Ka Zhang
Keyword(s):  
Computer Vision ◽  
Virtual Reality ◽  
High Precision ◽  
Point Cloud ◽  
Low Cost ◽  
Experimental Results ◽  
Affine Invariant ◽  
Invariant Features ◽  
Dense Point

The object of this research is to reconstruct 3D dense point cloud of geographical scene. With the technology and method of computer vision , first affine invariant features are extracted and matched, then cameras parameters and 3D dense point cloud are recovered and united under geographical reference. The experimental results show that this method with low cost and high precision of centimeters can satisfy the requirements of measurement, modeling and virtual reality.

scholarly journals Direction Oriented Block based Inpainting using Morphological Operations

2019 ◽  
Vol 8 (12) ◽  
pp. 2769-2774
Keyword(s):  
Image Processing ◽  
Basic Concept ◽  
Efficient Algorithm ◽  
Image Inpainting ◽  
Experimental Results ◽  
Background Information ◽  
Morphological Operations ◽  
Original Image ◽  
Computationally Efficient ◽  
Block Based

Inpainting is one of the wide growing area of image processing. Image inpainting is a technique to reconstruct the restored region using some background information and obtain the results very efficiently and effectively. The basic concept of image inpainting is to replace the unwanted object from the original image and to recover the image using some neighborhood pixels in an undetectable way. In this paper, we introduce an efficient algorithm for image inpainting i.e., Direction Oriented Block-Based using Morphological Operations approach. This algorithm gives better efficiency than the previously proposed algorithm. By this approach, we can inpaint large regions as well as recover small portions in an undetectable way. A more accurate patch will be found out by this proposed approach. The experimental results proved that our proposed work is more computationally efficient and effective compared to previous work.

scholarly journals Construction of Affine Invariant Functions in Spatial Domain

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Jianwei Yang ◽  
Yunjie Chen ◽  
Massimo Scalia
Keyword(s):  
Object Classification ◽  
Invariant Function ◽  
Spatial Domain ◽  
Closed Curve ◽  
Experimental Results ◽  
Transform Domain ◽  
Affine Invariant ◽  
Invariant Functions ◽  
Object Contour

Affine invariant functions are constructed in spatial domain. Unlike the previous affine representation functions in transform domain, these functions are constructed directly on the object contour without any transformation. To eliminate the effect of the choice of points on the contour, an affine invariant function using seven points on the contour is constructed. For objects with several separable components, a closed curve is derived to construct the affine invariant functions. Several experiments have been conducted to evaluate the performance of the proposed method. Experimental results show that the constructed affine invariant functions can be used for object classification.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

APLIKASI PENAJAMAN CITRAA STREET VIEW MENGGUNAKAN METODE GRAMD SCHMIDT SPECTRAL SHARPENING DAN HIGH PASS FILTERING

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Erna Verawati ◽  
Surya Darma Nasution ◽  
Imam Saputra
Keyword(s):  
Image Processing ◽  
Visual Information ◽  
Intensity Difference ◽  
Original Image ◽  
Filtering Method ◽  
The Road ◽  
Street View ◽  
Result Show ◽  
Filter Process ◽  
High Pass

Sharpening the image of the road display requies a degree of brightness in the process of sharpening the image from the original image result of the improved image. One of the sharpening of the street view image is image processing. Image processing is one of the multimedia components that plays an important role as a form of visual information. There are many image processing methods that are used in sharpening the image of street views, one of them is the gram schmidt spectral sharpening method and high pass filtering. Gram schmidt spectral sharpening method is method that has another name for intensity modulation based on a refinement fillter. While the high pass filtering method is a filter process that btakes image with high intensity gradients and low intensity difference that will be reduced or discarded. Researce result show that the gram schmidt spectral sharpening method and high pass filtering can be implemented properly so that the sharpening of the street view image can be guaranteed sharpening by making changes frome the original image to the image using the gram schmidt spectral sharpening method and high pass filtering.Keywords: Image processing, gram schmidt spectral sharpening and high pass filtering.

Secure Watermarking using Diophantine Equations for Authentication and Recovery

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Jayashree Nair ◽  
T. Padma
Keyword(s):  
Diophantine Equation ◽  
Diophantine Equations ◽  
Jpeg Compression ◽  
Authentication Scheme ◽  
Original Image ◽  
Invariant Features ◽  
Jpeg2000 Compression ◽  
Frequency Properties ◽  
Visual Authentication

This paper describes an authentication scheme that uses Diophantine equations based generation of the secret locations to embed the authentication and recovery watermark in the DWT sub-bands. The security lies in the difficulty of finding a solution to the Diophantine equation. The scheme uses the content invariant features of the image as a self-authenticating watermark and a quantized down sampled approximation of the original image as a recovery watermark for visual authentication, both embedded securely using secret locations generated from solution of the Diophantine equations formed from the PQ sequences. The scheme is mildly robust to Jpeg compression and highly robust to Jpeg2000 compression. The scheme also ensures highly imperceptible watermarked images as the spatio –frequency properties of DWT are utilized to embed the dual watermarks.

Sign in / Sign up

Export Citation Format

Share Document