Identification and inspection of 2-D objects using new moment-based shape descriptors

Sluzek, Andrzej

doi:10.1016/0167-8655(95)00021-8

Cited by 35 publications

(14 citation statements)

References 22 publications

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“…Mukundan and Ramakrishnan (1996), Mukundan and Malik (1993) applied them to estimate the position and the attitude of the object in 3-D space. Additionally in Sluzek (1995) it was proposed to use local moment invariants in industrial quality inspection and many authors used moment invariants for character recognition (Belkasim et al 1991;El-Khaly and Sid-Ahmed 1990;Tsirikolias and Mertzios 1993;Khotanzad and Hong 1990;Flusser and Suk 1994a). Maitra (1979) and Hupkens and de Clippeleir (1995) made them invariant also to contrast changes, Wang and Healey (1998) proposed illumination invariants particularly suitable for texture classification.…”

Section: State-of-the-art In Briefmentioning

confidence: 98%

Implicit Moment Invariants

2009

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The use of traditional moment invariants in object recognition is limited to simple geometric transforms, such as rotation, scaling and affine transformation of the image. This paper introduces so-called implicit moment invariants. Implicit invariants measure the similarity between two images factorized by admissible image deformations. For many types of image deformations traditional invariants do not exist but implicit invariants can be used as features for object recognition. In the paper we present implicit moment invariants with respect to polynomial transform of spatial coordinates, describe their stable and efficient implementation by means of orthogonal moments, and demonstrate their performance in artificial as well as real experiments.

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Section: State-of-the-art In Briefmentioning

confidence: 98%

Implicit Moment Invariants

2009

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“…Moments and functions of moments have been successfully and extensively used in pattern recognition, image classification and scene analysis applications [1][2][3][4][5][6][7][8][9]. Moreover, image moments have also been used for facial expression recognition [10], stereo image matching [11], image retrieval from databases [12] and image watermarking [13].…”

Section: Introductionmentioning

confidence: 99%

Parameterized real-time moment computation on gray images using block techniques

Spiliotis

Boutalis

2009

J Real-Time Image Proc

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Moments constitute a well-known tool in the field of image analysis and pattern recognition, but they suffer from the drawback of high computational cost. Efforts for the reduction of the required computational complexity have been reported, mainly focused on binary images, but recently some approaches for gray images have been also presented. In this study, we propose a simple but effective approach for the computation of gray image moments. The gray image is decomposed in a set of binary images. Some of these binary images are substituted by an ideal image, which is called ''half-intensity'' image. The remaining binary images are represented using the image block representation concept and their moments are computed fast using block techniques. The proposed method computes approximated moment values with an error of 2-3% from the exact values and operates in real time (i.e., video rate). The procedure is parameterized by the number m of ''half-intensity'' images used, which controls the approximation error and the speed gain of the method. The computational complexity is O(kL 2 ), where k is the number of blocks and L is the moment order.

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“…It attains good results in shape recognition. These various moment invariants have been successfully utilized as pattern features in a number of applications including character recognition [13,14], aircraft recognition [15], object identification and discrimination [16,17], content-based image retrieval [18], two-dimensional (2D) flow fields analysis [19], etc. [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study on Weighted Central Moment and Its Application in 2D Shape Retrieval

et al. 2016

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Moment invariants have been extensively studied and widely used in object recognition. The pioneering investigation of moment invariants in pattern recognition was due to Hu, where a set of moment invariants for similarity transformation were developed using the theory of algebraic invariants. This paper details a comparative analysis on several modifications of the original Hu moment invariants which are used to describe and retrieve two-dimensional (2D) shapes with a single closed contour. The main contribution of this paper is that we propose several different weighting functions to calculate the central moment according to human visual processing. The comparative results are detailed through experimental analysis. The results suggest that the moment invariants improved by weighting functions can get a better retrieval performance than the original one does.

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Identification and inspection of 2-D objects using new moment-based shape descriptors

Cited by 35 publications

References 22 publications

Implicit Moment Invariants

Implicit Moment Invariants

Parameterized real-time moment computation on gray images using block techniques

A Comparative Study on Weighted Central Moment and Its Application in 2D Shape Retrieval

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