Yong-Huai Huang

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.

Efficient sampling strategy and refinement strategy for randomized circle detection

Circle detection is fundamental in pattern recognition and computer vision. The randomized approach has received much attention for its computational benefit when compared with the Hough transform. In this paper, a multiple-evidence-based sampling strategy is proposed to speed up the randomized approach. Next, an efficient refinement strategy is proposed to improve the accuracy. Based on different kinds of ten test images, experimental results demonstrate the computation-saving and accuracy effects when plugging the proposed strategies into three existing circle detection methods.

Reversible Data Hiding-Based Approach for Intra-Frame Error Concealment in H.264/AVC

Error concealment plays an important role in robust video transmission. Recently, Chen and Leung presented an efficient data hiding-based (DH-based) approach to recover corrupted macroblocks from the intra-frame of an H.264/AVC sequence, but it suffers from the quality degradation problem. Since the quantized discrete cosine transform coefficients of an H.264/AVC sequence tend to form a Laplace distribution, we therefore propose a reversible DH-based approach for intra-frame error concealment based on this characteristic. Our design is able to achieve no quality degradation. Experimental results demonstrate that the quality of recovered video sequences obtained by our approach is indeed superior to that of the DH-based method. In addition, the quality advantage of our approach is illustrated when compared with the previous five related methods.

Capacity maximization for reversible data hiding based on dynamic programming approach

Abstract Recently, an efficient reversible lossless data hiding algorithm by Ni et al. was presented. Their fast algorithm can recover the original image without any distortion and its PSNR lower bound is higher than that of all existing reversible data hiding algorithms. Instead of selecting the peak-valley pairs in a greedy way, this paper presents a dynamic programming-based reversible data hiding algorithm to determine the most suitable peak-valley pairs such that the embedding capacity object can be maximized. Based on some artificial map images, experimental results demonstrate that our proposed algorithm has 9% embedding capacity improvement ratio and has the similar image quality performance when compared to Ni et al.’s algorithm although it has some execution-time degradation. For natural images, the embedding capacity of Ni et al.’s algorithm is very close to the maximal embedding capacity obtained by our proposed algorithm. Furthermore, the comparison between our proposed dynamic programming-based algorithm and the reversible data hiding algorithm by Chang et al. is investigated.

Speed up the computation of randomized algorithms for detecting lines, circles, and ellipses using novel tuning-and LUT-based voting platform

Abstract Shape detection is a fundamental problem in image processing field. In shape detection, lines, circles, and ellipses are the three most important features. In the past four decades, the robustness and the time speedup are two main concerned issues in most developed algorithms. Previously, many randomized algorithms were developed to speed up the computation of the relevant detection successfully. This paper does focus on the time speedup issue. Based on Bresenham’s drawing paradigm, this paper first presents a novel lookup table (LUT)-based voting platform. According to the proposed LUT-based voting platform, we next present a novel computational scheme to significantly speed up the computation of some existing randomized algorithms for detecting lines, circles, and ellipses. Moreover, the detailed time complexity analyses are provided for the three concerned features under our proposed computational scheme and these derived nontrivial analyses also show the relevant computational advantage. Under some real images, experimental results illustrate that our proposed computational scheme can significantly speed up the computation of some existing randomized algorithms. In average, the execution-time improvement ratios are about 28%, 56%, and 48% for detecting lines, circles, and ellipses, respectively, and these improvement ratios are vary close to the theoretic analyses.

Distortion reduction for histogram modification-based reversible data hiding

Abstract The histogram modification (HM) method proposed by Ni et al. is very efficient for reversible data hiding (RDH). Besides the excellent execution-time performance, Ni et al.’s HM-based RDH (HMRDH) method has a high PSNR lower bound of marked images. In this short communication, an observation on Ni et al.’s HM-based RDH (HMRDH) method is pointed out that the distortion of the marked image from Ni et al.’s method is dependent on the number of 1’s in the watermark. From this observation, we first present a watermark complement scheme to reduce the distortion occurred in Ni et al.’s HMRDH method. Later, combinatorial analysis for average distortion ratio of the proposed scheme is provided. This analysis motivates us to present a block-based complement scheme to improve the distortion reduction further. The tradeoff between the distortion and the number of partitioned blocks is also investigated. Taking nine well-known trademarks as the test watermarks and two cover images with different types of content, experimental results demonstrated the distortion reduction and higher PSNR lower bound advantages of the proposed block-based watermark complement scheme.

Efficient symmetry-based screening strategy to speed up randomized circle-detection

Randomized approaches for circle detections are often used for the advantages of less computational time and memory requirements. However, randomized approaches involve examining a large number of candidate circles and may not be suitable for real-time applications. In this paper, a screening strategy based on the symmetric property of the circle is adopted to select the promising candidates for further investigation, resulting in substantial reduction in the computational time while maintaining the accuracy. Empirical results show that, under the same accuracy level, the proposed symmetry-based method achieves the improvement ratios of 40%-90% on the execution-time when compared to four state-of-the-art randomized methods.

New orientation-based elimination approach for accurate line-detection

Detecting lines correctly from a digital image is an important crucial step in many real-word applications. In this paper, we present an orientation-based strategy to filter out those inappropriate edge pixels before performing the line-detection task. Due to the effective strategy, both the memory size and the computation time are significantly reduced during a Hough transform-based detection process. Further, the proposed elimination strategy can also speed up the randomized-based detection process. Taking four previously developed line-detection techniques as comparison targets, experimental results have shown that our proposed orientation-based elimination strategy is superior to the previous line-detection methods in terms of memory requirement and computation time.

Fast randomized algorithm for center-detection

Recently, Cauchie et al. presented an adaptive Hough transform-based algorithm to successfully solve the center-detection problem which is an important issue in many real-world problems. This paper presents a fast randomized algorithm to solve the same problem. With similar memory requirement and accuracy, the computational complexity analysis and comparison show that our proposed algorithm performs much better in terms of efficiency. We have tested our algorithm on 13 real images. Experimental results indicated that our algorithm has 38% execution-time improvement over Cauchie et al.s algorithm. The extension of the proposed algorithm to detect multiple centers is also addressed.