Kuo-Liang Chung

An Efficient Randomized Algorithm for Detecting Circles

Detecting circles from a digital image is very important in shape recognition. In this paper, an efficient randomized algorithm (RCD) for detecting circles is presented, which is not based on the Hough transform (HT). Instead of using an accumulator for saving the information of the related parameters in the HT-based methods, the proposed RCD does not need an accumulator. The main concept used in the proposed RCD is that we first randomly select four edge pixels in the image and define a distance criterion to determine whether there is a possible circle in the image; after finding a possible circle, we apply an evidence-collecting process to further determine whether the possible circle is a true circle or not. Some synthetic images with different levels of noises and some realistic images containing circular objects with some occluded circles and missing edges have been taken to test the performance. Experimental results demonstrate that the proposed RCD is faster than other HT-based methods for the noise level between the light level and the modest level. For a heavy noise level, the randomized HT could be faster than the proposed RCD, but at the expense of massive memory requirements.

A novel SVD- and VQ-based image hiding scheme

Abstract This paper presents a novel singular value decomposition (SVD)- and vector quantization (VQ)-based image hiding scheme to hide image data. Plugging the VQ technique into the SVD-based compression method, the proposed scheme leads to good compression ratio and satisfactory image quality. Experimental results show that the embedding image is visually indistinguishable from the stego-image.

Efficient Shadow Detection of Color Aerial Images Based on Successive Thresholding Scheme

Recently, Tsai presented an efficient algorithm which uses the ratio value of the hue over the intensity to construct the ratio map for detecting shadows of color aerial images. Instead of only using the global thresholding process in Tsais algorithm, this paper presents a novel successive thresholding scheme (STS) to detect shadows more accurately. In our proposed STS, the modified ratio map, which is obtained by applying the exponential function to the ratio map proposed by Tsai, is presented to stretch the gap between the ratio values of shadow and nonshadow pixels. By performing the global thresholding process on the modified ratio map, a coarse-shadow map is constructed to classify the input color aerial image into the candidate shadow pixels and the nonshadow pixels. In order to detect the true shadow pixels from the candidate shadow pixels, the connected component process is first applied to the candidate shadow pixels for grouping the candidate shadow regions. For each candidate shadow region, the local thresholding process is performed iteratively to extract the true shadow pixels from the candidate shadow region. Finally, for the remaining candidate shadow regions, a fine-shadow determination process is applied to identify whether each remaining candidate shadow pixel is the true shadow pixel or not. Under six testing images, experimental results show that, for the first three testing images, both Tsais and our proposed algorithms have better detection performance than that of the algorithm of Huang et al., and the shadow detection accuracy of our proposed STS-based algorithm is comparable to Tsais algorithm. For the other three testing images, which contain some low brightness objects, our proposed algorithm has better shadow detection accuracy when compared with the previous two shadow detection algorithms proposed by Huang et al. and Tsai.

On SVD-based watermarking algorithm

This short communication presents two notes for singular value decomposition (SVD)-based watermarking scheme. The presented notes can increase the invisibility and capacity when embedding the watermark into U and V components of the SVD.

Large encrypting binary images with higher security

In this paper, we present a new approach for encrypting binary images. Putting different scan patterns at the same level in the scan tree structure and employing a two-dimensional run-encoding (2DRE) technique, our encryption method can encrypt images with higher security and good compression ratio when compared to the previous results. Detailed security analysis from the combinatorial viewpoint is also given. Some experimentations are carried out to illustrate the good performance of our proposed method.

Demosaicing of Color Filter Array Captured Images Using Gradient Edge Detection Masks and Adaptive Heterogeneity-Projection

Without demosaicing processing, this paper first proposes a new approach to extract more accurate gradient/edge information on mosaic images directly. Next, based on spectral-spatial correlation, a novel adaptive heterogeneity-projection with proper mask size for each pixel is presented. Combining the extracted gradient/edge information and the adaptive heterogeneity-projection values, a new edge-sensing demosaicing algorithm is presented. Based on 24 popular testing images, experimental results demonstrated that our proposed high-quality demosaicing algorithm has the best image quality performance when compared with several recently published algorithms.

A new predictive search area approach for fast block motion estimation

According to the observation on the distribution of motion differentials among the motion vector of any block and those of its four neighboring blocks from six real video sequences, this paper presents a new predictive search area approach for fast block motion estimation. Employing our proposed simple predictive search area approach into the full search (FS) algorithm, our improved FS algorithm leads to 93.83% average execution-time improvement ratio, but only has a small estimation accuracy degradation. We also investigate the advantages of computation and estimation accuracy of our improved FS algorithm when compared to the edge-based search algorithm of Chan and Siu; experimental results reveal that our improved FS algorithm has 74.33% average execution-time improvement ratio and has a higher estimation accuracy. Finally, we further compare the performance among our improved FS algorithm, the three-step search algorithm, and the block-based gradient descent search algorithm.

The complex Householder transform

The Householder (1968) transform is very useful in matrix computations and signal processing. A straightforward derivation for a complex Householder transform is given. It needs fewer complex operations when compared with the previous results by Venkaiah et al. (1993) and Xia and Suter (see Digital Signal Process., vol.5, p.116-17, 1995). We also investigate applying our result to the derivation of a hyperbolic Householder transform.

Inverse halftoning algorithm using edge-based lookup table approach

The inverse halftoning algorithm is used to reconstruct a gray image from an input halftone image. Based on the recently published lookup table (LUT) technique, this paper presents a novel edge-based LUT method for inverse halftoning which improves the quality of the reconstructed gray image. The proposed method first uses the LUT-based inverse halftoning method as a preprocessing step to transform the given halftone image to a base gray image, and then the edges are extracted and classified from the base gray image. According to these classified edges, a novel edge-based LUT is built up to reconstruct the gray image. Based on a set of 30 real training images with both low- and high-frequency contents, experimental results demonstrated that the proposed method achieves a better image quality when compared to the currently published two methods, by Chang et al. and Mes

Efficient sampling strategy and refinement strategy for randomized circle detection

80e and Vaidyanathan.