June-Suh Cho

Bio: June-Suh Cho is an academic researcher from Hankuk University of Foreign Studies. The author has contributed to research in topics: Cognitive neuroscience of visual object recognition & Card reader. The author has an hindex of 1, co-authored 5 publications receiving 19 citations.

Contour-based partial object recognition using symmetry in image databases

Abstract: 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 the contours of objects. Our 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 classification tree. 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.

Recognition of Partially Occluded Elliptical Objects using Symmetry on Contour

Abstract: There are many research efforts in object recognition. Most existing methods for object recognition are based on full objects. However, many images contain multiple objects with occluded shapes and regions. Due to the occlusion of objects, image retrieval can provide incomplete, uncertain, and inaccurate results. To resolve this problem, we propose a new method to reconstruct objects using symmetry properties since most objects in a given image database are represented by symmetrical figures. Even though there have been several efforts in object recognition with occlusion, current methods have been highly sensitive to object pose, rotation, scaling, and visible portion of occluded objects. In addition, many appearance-based and model-based object recognition methods assumed that they have known occluded regions of objects or images through extensive training processes with statistical approach. However, our new approach is not limited to recognizing occluded objects by pose and scale changes, and does not need extensive training processes. Unlike existing methods, the proposed method finds shapes and regions to reconstruct occluded shapes and regions within objects. We assume that we only consider the elliptical objects in recognition. The proposed approach can handle object rotation and scaling for dealing with occlusion, and does not require extensive training processes. The main advantage of our proposed approach is that it becomes simple to reconstruct objects from occlusions using symmetry. We present a robust method, which is based on the contours of objects, for recognizing partially occluded objects based on symmetry properties. The contour-based approach finds a symmetry axis using the maximum diameter from the occluded object. In experiments, we demonstrate how a proposed method reconstructs and recognizes occluded shapes and regions using symmetry. Experiments use rotated and scaled objects for dealing with occlusion. We use mirror symmetry to find possible occluded regions in objects. Examples of partially occluded objects are shown in Figure 1.1. We also evaluate the recognition rate of the reconstructed objects using symmetry and the visible portion of the occluded objects for recognition. The method produces average recognition rates for cups and plates above 88% with 30% occlusion. In this case, part of the

Virtual magnetic line strip type ic card being readable with card reader for magnetic cards

Abstract: A virtual magnetic line strip type IC card being capable to be read by a magnetic strip card reader is provided. An information transmission controller reads out a value in the card in¬ formation from a card information storing device and outputs a pulse signal corresponding to a magnitude of the value. A magnetic current driving device generates an analog magnetic driving current corresponding to the change of magnitude of the pulse signal from the information transmission controller. A magnetic transmitter transmits a time-varying magnetic field cor¬ responding to polarity changes of the magnetic driving current at predetermined locations cor¬ responding to tracks by the magnetic strip card standard. The time-varying magnetic field is read by a magnetic line strip type card reader. An alignment detector detects aligning of the magnetic head of the card reader and the head of the magnetic transmitter, and an ID confirmation device verifies users using the user's fingerprint or password. The IC card can be used without incurring any change to the card readers for the magnetic line strip type cards. Also, a single physical IC card can function as many logical IC cards by storing a plurality of card information therein.

Splitting Rules using Intervals for Object Classification in Image Databases

Abstract: The way to assign a splitting criterion for correct object classification is the main issue in all decisions trees. This paper describes new splitting rules for classification in order to find an optimal split point. Unlike the current splitting rules that are provided by searching all threshold values, this paper proposes the splitting rules that we based on the probabilities of pre assigned intervals. Our methodology provides that user can control the accuracy of tree by adjusting the number of intervals. In addition, we applied the proposed splitting rules to a set of image data that was retrieved by parameterized feature extraction to recognize image objects.

Automatic Semantic Annotation of Real-World Web Images

Abstract: As the number of Web images is increasing at a rapid rate, searching them semantically presents a significant challenge. Many raw images are constantly uploaded with little meaningful direct annotations of semantic content, limiting their search and discovery. In this paper, we present a semantic annotation technique based on the use of image parametric dimensions and metadata. Using decision trees and rule induction, we develop a rule-based approach to formulate explicit annotations for images fully automatically, so that by the use of our method, semantic query such as "sunset by the sea in autumn in New York" can be answered and indexed purely by machine. Our system is evaluated quantitatively using more than 100,000 Web images. Experimental results indicate that this approach is able to deliver highly competent performance, attaining good recall and precision rates of sometimes over 80%. This approach enables a new degree of semantic richness to be automatically associated with images which previously can only be performed manually.

System and method for a baseband nearfield magnetic stripe data transmitter

Abstract: The present invention describes a system and a method for a baseband near-field magnetic stripe data transmitter (MST) device that transmits payment card data from a smart-phone, or other electronic device, into a Point of Sale (POS) transaction terminal. The MST device includes a driver and an inductor. The MST receives magnetic stripe data comprising payment card data, processes the received magnetic stripe data and emits high energy magnetic pulses comprising the processed magnetic stripe data that are then received remotely by the magnetic stripe reader of the POS.

A Mayer–Vietoris Formula for Persistent Homology with an Application to Shape Recognition in the Presence of Occlusions

Abstract: In algebraic topology it is well known that, using the Mayer–Vietoris sequence, the homology of a space X can be studied by splitting X into subspaces A and B and computing the homology of A, B, and A∩B. A natural question is: To what extent does persistent homology benefit from a similar property? In this paper we show that persistent homology has a Mayer–Vietoris sequence that is generally not exact but only of order 2. However, we obtain a Mayer–Vietoris formula involving the ranks of the persistent homology groups of X, A, B, and A∩B plus three extra terms. This implies that persistent homological features of A and B can be found either as persistent homological features of X or of A∩B. As an application of this result, we show that persistence diagrams are able to recognize an occluded shape by showing a common subset of points.

Apparatus, method and computer program for determining information about shape and/or location of an ellipse in a graphical image

Abstract: An apparatus for determining information about shape and location of an ellipse involves determining two coordinates of a first ellipse point representing a point of the ellipse located furthest in the first direction, and determining two coordinates of a second ellipse point representing a point of the ellipse located furthest in a direction opposite to the first direction. The apparatus determines parameters of bent line segments approximating the ellipse at ellipse points or in a surrounding of ellipse points, and determines the coordinates of ellipse points based on the parameters of the bent line segments. The apparatus involves calculating ellipse parameters of the ellipse based on the two coordinates of the first ellipse point and the two coordinates of the second ellipse point. The apparatus enables real-time-capable determination of parameters of an ellipse included in an image to be analyzed.

Image matching using Gradient Orientation Selective Cross Correlation

Abstract: Image matching has been an important topic in computer vision and image processing. A new approach named Gradient Orientation Selective Cross Correlation is proposed for image matching. In the new approach, a gradient orientation selectivity strategy is proposed to exclude the wrong points from correlation, especially for partial occlusion and some other ill-conditions. Experimental results are shown to demonstrate robustness, efficiency, and accuracy of the algorithm.