Whoi-Yul Kim

A region-based shape descriptor using Zernike moments

In order to retrieve an image from a large image database, the descriptor should be invariant to scale and rotation. It must also have enough discriminating power and immunity to noise for retrieval from a large image database. The Zernike moment descriptor has many desirable properties such as rotation invariance, robustness to noise, expression efficiency, fast computation and multi-level representation for describing the shapes of patterns. In this paper, we show that the Zernike moment can be used as an effective descriptor of global shape of an image in a large image database. The experimental results conducted on a database of about 6,000 images in terms of exact matching under various transformations and the similarity-based retrieval show that the proposed shape descriptor is very effective in representing shapes.

A novel approach to the fast computation of Zernike moments

This paper presents a novel approach to the fast computation of Zernike moments from a digital image. Most existing fast methods for computing Zernike moments have focused on the reduction of the computational complexity of the Zernike 1-D radial polynomials by introducing their recurrence relations. Instead, in our proposed method, we focus on the reduction of the complexity of the computation of the 2-D Zernike basis functions. As Zernike basis functions have specific symmetry or anti-symmetry about the x-axis, the y-axis, the origin, and the straight line y=x, we can generate the Zernike basis functions by only computing one of their octants. As a result, the proposed method makes the computation time eight times faster than existing methods. The proposed method is applicable to the computation of an individual Zernike moment as well as a set of Zernike moments. In addition, when computing a series of Zernike moments, the proposed method can be used with one of the existing fast methods for computing Zernike radial polynomials. This paper also presents an accurate form of Zernike moments for a discrete image function. In the experiments, results show the accuracy of the form for computing discrete Zernike moments and confirm that the proposed method for the fast computation of Zernike moments is much more efficient than existing fast methods in most cases.

A novel two stage template matching method for rotation and illumination invariance

Abstract Template matching is the process of determining the presence and the location of a reference image or an object inside a scene image under analysis by a spatial cross-correlation process. Conventional cross-correlation type algorithms are computationally expensive. Furthermore, when the object in the image is rotated, the conventional algorithms cannot be used for practical purposes. In this paper, an algorithm for a rotation invariant template matching method based on the combination of the projection method and Zernike moments is proposed. The algorithm consists of two stages. In the first stage, the matching candidates are selected using a computationally low cost feature. Frequency domain calculation was adopted to reduce the computational cost for this stage. In the second stage, rotation invariant template matching is performed only on the matching candidates using Zernike moments.

Hydrochromic conjugated polymers for human sweat pore mapping

Hydrochromic materials have been actively investigated in the context of humidity sensing and measuring water contents in organic solvents. Here we report a sensor system that undergoes a brilliant blue-to-red colour transition as well as ‘Turn-On’ fluorescence upon exposure to water. Introduction of a hygroscopic element into a supramolecularly assembled polydiacetylene results in a hydrochromic conjugated polymer that is rapidly responsive (<20 μs), spin-coatable and inkjet-compatible. Importantly, the hydrochromic sensor is found to be suitable for mapping human sweat pores. The exceedingly small quantities (sub-nanolitre) of water secreted from sweat pores are sufficient to promote an instantaneous colorimetric transition of the polymer. As a result, the sensor can be used to construct a precise map of active sweat pores on fingertips. The sensor technology, developed in this study, has the potential of serving as new method for fingerprint analysis and for the clinical diagnosis of malfunctioning sweat pores.

Robust rotation angle estimator

The conventional method of estimating the rotation angle of a pattern using the principal axes is not suitable for circular symmetric patterns since their eigenvalues are similar in both directions. In the paper, a robust method of estimating a rotation angle using the phase information of Zernike moments is presented. The experimental results show that the proposed method estimates the rotation angle of the circular symmetric patterns more accurately than the principal axes method, even in the presence of noise.

A practical pattern recognition system for translation, scale and rotation invariance

We present a practical pattern recognition system that is invariant with respect to translation, scale and rotation of objects. The system is also insensitive to large variations of the threshold used. As feature vectors, Zernike moments are used and we compare them with Hus seven moment invariants. For a practical machine vision system, three key issues are discussed: pattern normalization, fast computation of Zernike moments, and classification using k-NN rule. As testing results, the system recognizes a set of 62 alphanumeric machine-printed characters with different sizes, at arbitrary orientations, and with different thresholds where the size of the characters varies from 10/spl times/10 to 512/spl times/512 pixels.<<ETX>>

Rapid eye detection method for non-glasses type 3D display on portable devices

Eye detection is a critical task in many applications, especially for portable single user 3D display systems of the non-glasses type. However, existing methods either have high computational complexity or a low detection rate. In addition, these methods do not work with those using eye glasses for portable devices. In this paper, we propose a rapid eye detection method for portable devices. We propose a novel operator that measures contrast features to compute the difference in intensity between the iris region and its neighboring regions. The probability of an identified area being the eye position is calculated by our proposed contrast operator and the a priori geometric information of the two eyes. Experimental results show that the proposed method successfully detects the eyes in facial images regardless of illumination changes or wearing glasses. The average accuracy of the proposed method is 92.7%, which is higher than conventional methods. In addition, the proposed method can be run at an average rate of 12 fps on a portable device.

Automatic video summarizing tool using MPEG-7 descriptors for personal video recorder

We introduce an automatic video summarizing tool (AVST) for a personal video recorder. The tool utilizes MPEG-7 visual descriptors to generate a video index for a summary. The resulting index generates not only a preview of a movie but also allows non-linear access with thumbnails. In addition, the index supports the searching of shots similar to a desired one within saved video sequences. Moreover, simple shot-based video editing can readily be achieved using the generated index.

Fast and efficient method for computing ART

Angular radial transform (ART), which is the region-based shape descriptor of MPEG-7, has desirable properties for representing shape information in a small number of features with no redundancy. However, in order for ART to be useful, especially in limited computing environments, the computational cost of ART must be greatly reduced. In this paper, we derive symmetric/antisymmetric properties from the basis functions of ART and present a fast and efficient method to compute the ART coefficients using these properties. The proposed method significantly reduces the number of sinusoidal operations and multiplications in computing the coefficients of ART. Moreover, the memory requirements needed to store the ART basis functions in lookup tables are only 25% of the conventional method. The experimental results are presented to show the effectiveness of the proposed method.

Long range eye gaze tracking system for a large screen

Eye gaze tracking system has been widely researched for the replacement of the conventional computer interfaces such as the mouse and keyboard. In this paper, we propose the long range binocular eye gaze tracking system that works from 1.5 m to 2.5 m with allowing a head displacement in depth. The 3D position of the users eye is obtained from the two wide angle cameras. A high resolution image of the eye is captured using the pan, tilt, and focus controlled narrow angle camera. The angles for maneuvering the pan and tilt motor are calculated by the proposed calibration method based on virtual camera model. The performance of the proposed calibration method is verified in terms of speed and convenience through the experiment. The narrow angle camera keeps tracking the eye while the user moves his head freely. The point-of-gaze (POG) of each eye onto the screen is calculated by using a 2D mapping based gaze estimation technique and the pupil center corneal reflection (PCCR) vector. PCCR vector modification method is applied to overcome the degradation in accuracy with displacements of the head in depth. The final POG is obtained by the average of the two POGs. Experimental results show that the proposed system robustly works for a large screen TV from 1.5 m to 2.5 m distance with displacements of the head in depth (+20 cm) and the average angular error is 0.69°.