• The KIPS Transactions:PartB
• /
• v.13B no.2 s.105
• /
• pp.115-120
• /
• 2006

In This Paper, We Propose The Method To Reconstruct And Estimate Partially Occluded Elliptical Objects In Images From Overlapping And Cutting. We Present The Robust Method For Recognizing Partially Occluded Objects Based On Symmetry Properties, Which Is Based On The Contours Of Elliptical Objects. A Proposed Method Provides Simple Techniques To Reconstruct Occluded Regions Via A Region Copy Using The Symmetry Axis Within An Object. Based On The Estimated Parameters For Partially Occluded Objects, We Perform Object Recognition On The Classifier. Since A Proposed Method Relies On Reconstruction Of The Object Based On The Symmetry Properties Rather Than Statistical Estimates, It Has Proven To Be Remarkably Robust In Recognizing Partially Occluded Objects In The Presence Of Scale Changes, Object Pose, And Rotated Objects With Occlusion, Even Though h Proposed Method Has Minor Limitations Of Object Poses.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10b
• /
• pp.786-789
• /
• 1988

Partially occluded objects are recognized from a 2-D image through the use of maximum curvature points on the image boundary. The vertices of high curvature on an occluded object are classified by the objects which are hypothesized to be involved in the occlusion. A heuristic method is developed for computational speed. Two typical examples are given to illustrate the accuracy as well as the simplicity of the heuristic method.

• Journal of information and communication convergence engineering
• /
• v.13 no.4
• /
• pp.275-279
• /
• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

• The KIPS Transactions:PartB
• /
• v.15B no.2
• /
• pp.81-86
• /
• 2008

This paper discusses the problem of partial object recognition in image databases. We propose the method to reconstruct and estimate partially occluded shapes and regions of objects in images from overlapping and cutting. We present the robust method for recognizing partially occluded objects based on symmetry properties, which is based on an ellipse of objects. Our method provides simple techniques to reconstruct occluded regions via a region copy using the symmetry axis within an object. Since our method relies on reconstruction of the object based on the symmetry rather than statistical estimates, it has proven to be remarkably robust in recognizing partially occluded objects in the presence of scale changes, rotation, and viewpoint changes.

• International Journal of Contents
• /
• v.2 no.3
• /
• pp.22-26
• /
• 2006

In this paper we introduce a new circle detection algorithm for occluded on/off pupil and iris boundary extraction. The proposed algorithm employs 7-step processing to detect a center and radius of occluded on/off eye images using the property of the chords. The algorithm deals with two types of occluded pupil and iris boundary information; one is composed of circle-shaped, incomplete objects, which is called occluded on iris images and the other type consists of arc objects in which circular information has partially disappeared, called occluded off iris images. This method shows that the center and radius of iris boundary can be detected from as little as one-third of the occluded on/off iris information image. It is also shown that the proposed algorithm computed the center and radius of the incomplete iris boundary information which has partially occluded and disappeared. Experimental results on RGB images and IR images show that the proposed method has encouraging performance of boundary detection for pupil and iris segmentation. The experimental results show satisfactorily the detection of circle from incomplete circle shape information which is occluded as well as the detection of pupil/iris boundary circle of the occluded on/off image.

• The Journal of Society for e-Business Studies
• /
• v.26 no.2
• /
• pp.83-94
• /
• 2021

The need for recognition of partially occluded objects is increasing in the area of computer vision applications. Occlusion causes significant problems in identifying and locating an object. In this paper, an annealed Hopfield network (AHN) is proposed for detecting threat objects in passengers' check-in baggage. AHN is a deterministic approximation that is based on the hybrid Hopfield network (HHN) and annealing theory. AHN uses boundary features composed of boundary points and corner points which are extracted from input images of threat objects. The critical temperature also is examined to reduce the run time of AHN. Extensive computational experiments have been conducted to compare the performance of the AHNwith that of the HHN.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.8
• /
• pp.119-128
• /
• 1994

In this paper we propose a new method for the recognition of 2-D partially occluded objects. The border of the object is transformed to a curve in arc length-accumulated interior angle plane. The transformed curve of an image is partitioned so that each segment is bounded by the concave interior angles. In order to tolerate shape distortion due to the polygonal approximation of the boundary of the object a group of feature points of the input image are matched with those of model views. The estimation method for positions and orientations of the identified objects objects is presented.

• Journal of the Optical Society of Korea
• /
• v.12 no.2
• /
• pp.88-92
• /
• 2008

This paper discusses a photon-counting linear discriminant analysis (LDA) with computational integral imaging (II). The computational II method reconstructs three-dimensional (3D) objects on the reconstruction planes located at arbitrary depth-levels. A maximum likelihood estimation (MLE) can be used to estimate the Poisson parameters of photon counts in the reconstruction space. The photon-counting LDA combined with the computational II method is developed in order to classify partially occluded objects with photon-limited images. Unknown targets are classified with the estimated Poisson parameters while reconstructed irradiance images are trained. It is shown that a low number of photons are sufficient to classify occluded objects with the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.7
• /
• pp.190-198
• /
• 1994

In this paper, we propose the cross-section processing method which is simple in describing the SHGC of objects in a range image and which can describe the SHGC of occluded objects for the recognition of 3D objects. This method produces the cross-sections of an object along the assumed axis of the SHGC and describes the SHGC of the object by processing the produced cross-sections of the object using $\psi$ -S curves with invariant properties in position and size. Our method is simple in a process and can descirbe the SHGC of partially occluded objects because it uses range images with 3-D informations of objects without matching contours of objects with a model base. Thus it is a useful description method of a range image for the recognition of 3D objects shaped in SHGC form and we proved the usefulness of it in experiments.

• Journal of the Optical Society of Korea
• /
• v.19 no.3
• /
• pp.248-254
• /
• 2015

In this paper we propose an improved version of the computational integral imaging reconstruction (CIIR) for visualizing a partially occluded object by utilizing an image inpainting technique. In the proposed method the elemental images for a partially occluded three-dimensional (3D) object are recorded through the integral imaging pickup process. Next, the depth of occlusion within the elemental images is estimated using two different CIIR methods, and the weight mask pattern for occlusion is generated. After that, we apply our image inpainting technique to the recorded elemental images to fill in the occluding area with reliable data, using information from neighboring pixels. Finally, the inpainted elemental images for the occluded region are reconstructed using the CIIR process. To verify the validity of the proposed system, we carry out preliminary experiments in which faces are the objects. The experimental results reveal that the proposed system can dramatically improve the quality of a reconstructed CIIR image.