A New Method for Recognition Partially Occluded Curved Objects under Affine Transformation

Zhang, Guimei; Jiyuan, Xu; Liu, Jianxin

doi:10.1109/iske.2015.52

Cited by 8 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As previously stated, the input frame's fabric may experience shearing or translation even if the capturing camera and input frame are maintained in the ideal location. Consequently, affine transformation is performed on the input image frame [17]. The produced transformed image will be utilized in the subsequent steps.…”

Section: Affine Transformationmentioning

confidence: 99%

An Inventive Method to Fabric Part Structural Defect Detection Using Frame Harmonizing

Dhivya¹,

Suganthi²

2022

ijcci

View full text Add to dashboard Cite

Using a frame harmonizing based approach, this paper examines paper defects. In the textiles industry, the quick cutting and sewing of fabric has resulted in a lot of small mistakes, making this task extremely difficult. Especially these deformities won't be quickly recognized by specialists as well as programming. A novel frame harmonizing method is used in our system to find flaws in the fabric production process. Transformation and filtering techniques are used for the inputted fabric image frame. The conventional outline extraction method Berkeley edge detector is used to extract the edge map. Contour-based features are extracted and classified by K-Nearest Neighbour (KNN) classifier. The experimentation with real-time data set produced the outstanding performance results when compared with state of the art methods.

show abstract

Section: Affine Transformationmentioning

confidence: 99%

An Inventive Method to Fabric Part Structural Defect Detection Using Frame Harmonizing

Dhivya¹,

Suganthi²

2022

ijcci

View full text Add to dashboard Cite

show abstract

“…The performance of the detection algorithm is susceptible to noise, feature dimensions, and feature descriptors. The robust Hausdorff distance is used to evaluate the similarity between the model feature point set and the object feature point set [9]. However, it is sensitive to noise and only suitable for objects with smooth surface boundaries.…”

Section: Introductionmentioning

confidence: 99%

“…In image processing, the polygon approximation method is often used to replace the curve with multiple line segments to simplify the contour model, and still reserve the key information of the contour. The contour feature of the polygon approximation is more robust to image noise than the point set feature in [9], and has a higher feature matching efficiency. The polygon approximation method for the contour feature is proposed to extract two variables as the angle and the length to improve the anti-interference ability and reduce the contour model complexity.…”

Section: Introductionmentioning

confidence: 99%

CHMM Object Detection Based on Polygon Contour Features by PSM

Zhuo¹,

Huang²

2022

Preprint

View full text Add to dashboard Cite

Since the conventional split-merge algorithm is sensitive to the object scale variance and splitting starting point, a piecewise split-merge polygon approximation method is proposed to extract the object contour features. Specifically, the contour corner is used as the starting point for the contour piecewise approximation to reduce the sensitivity of the contour segment on the starting point; then, the split-merge algorithm is used to implement the polygon approximation for each contour segments. Both the distance ratio and the arc length ratio instead of the distance error are used as the iterative stop condition to improve the robustness to the object scale variance. Both the angle and length as two features describe the shape of the contour polygon, and affect each other along the contour order relationship. Since they have a strong coupling relationship. To improve the description correction of the contour, these two features are combined to construct a Coupled Hidden Markov Model to detect the object by calculating the probability of the contour feature. The proposed algorithm is validated on ETHZ Shape Classes and INRIA Horses standard datasets. Compared with other contour-based object detection algorithms, the proposed algorithm reduces the complexity of contour description, improves the robustness of contour features to scale variance, and has a higher object detection rate.

show abstract

Partial Contour Matching Based on Affine Curvature Scale Space Descriptors

Elghoul

Ghorbel

2021

New Approaches for Multidimensional Signal Processing

View full text Add to dashboard Cite

A New Method for Recognition Partially Occluded Curved Objects under Affine Transformation

Cited by 8 publications

References 9 publications

An Inventive Method to Fabric Part Structural Defect Detection Using Frame Harmonizing

An Inventive Method to Fabric Part Structural Defect Detection Using Frame Harmonizing

CHMM Object Detection Based on Polygon Contour Features by PSM

Partial Contour Matching Based on Affine Curvature Scale Space Descriptors

Contact Info

Product

Resources

About