• Title/Summary/Keyword: dominant edge extraction

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Regional Linear Warping for Image Stitching with Dominant Edge Extraction

  • Yoo, Jisung;Hwang, Sung Soo;Kim, Seong Dae;Ki, Myung Seok;Cha, Jihun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.10
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    • pp.2464-2478
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    • 2013
  • Image stitching techniques produce an image with a wide field-of-view by aligning multiple images with a narrow field-of-view. While conventional algorithms successfully stitch images with a small parallax, structure misalignment may occur when input images contain a large parallax. This paper presents an image stitching algorithm that aligns images with a large parallax by regional linear warping. To this end, input images are first approximated as multiple planar surfaces, and different linear warping is applied to each planar surface. For approximating input images as multiple planar surfaces, the concept of dominant edges is introduced. Dominant edges are defined as conspicuous edges of lines in input images, and extracted dominant edges identify the boundaries of each planar surface. Dominant edge extraction is conducted by detecting distinct changes of local characteristics around strong edge pixels. Experimental results show that the proposed algorithm successfully stitches images with a large parallax without structure misalignment.

Automatic Extraction of Rescue Requests from Drone Images: Focused on Urban Area Images (드론영상에서 구조요청자 자동추출 방안: 도심지역 촬영영상을 중심으로)

  • Park, Changmin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.3
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    • pp.37-44
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    • 2019
  • In this study, we propose the automatic extraction method of Rescue Requests from Drone Images. A central object is extracted from each image by using central object extraction method[7] before classification. A central object in an images are defined as a set of regions that is lined around center of the image and has significant texture distribution against its surrounding. In this case of artificial objects, edge of straight line is often found, and texture is regular and directive. However, natural object's case is not. Such characteristics are extracted using Edge direction histogram energy and texture Gabor energy. The Edge direction histogram energy calculated based on the direction of only non-circular edges. The texture Gabor energy is calculated based on the 24-dimension Gebor filter bank. Maximum and minimum energy along direction in Gabor filter dictionary is selected. Finally, the extracted rescue requestor object areas using the dominant features of the objects. Through experiments, we obtain accuracy of more than 75% for extraction method using each features.

Recovery of the connection relationship among planar objects

  • Yao, Fenghui;Shao, Guifeng;T amaki, Akikazu;Kato, Kiyoshi
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.430-433
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    • 1996
  • The shape of an object plays a very important role in pattern analysis and classification. Roughly, the researches on this topic can be classified into three fields, i.e. (i) edge detection, (ii) dominant points extraction, and (iii) shape recognition and classification. Many works have been done in these three fields. However, it is very seldom to see the research that discusses the connection relationship of objects. This problem is very important in robot assembly systems. Therefore, here we focus on this problem and discuss how to recover the connection relationship of planar objects. Our method is based on the partial curve identification algorithm. The experiment results show the efficiency and validity of this method.

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Correction of Signboard Distortion by Vertical Stroke Estimation

  • Lim, Jun Sik;Na, In Seop;Kim, Soo Hyung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.9
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    • pp.2312-2325
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    • 2013
  • In this paper, we propose a preprocessing method that it is to correct the distortion of text area in Korean signboard images as a preprocessing step to improve character recognition. Distorted perspective in recognizing of Korean signboard text may cause of the low recognition rate. The proposed method consists of four main steps and eight sub-steps: main step consists of potential vertical components detection, vertical components detection, text-boundary estimation and distortion correction. First, potential vertical line components detection consists of four steps, including edge detection for each connected component, pixel distance normalization in the edge, dominant-point detection in the edge and removal of horizontal components. Second, vertical line components detection is composed of removal of diagonal components and extraction of vertical line components. Third, the outline estimation step is composed of the left and right boundary line detection. Finally, distortion of the text image is corrected by bilinear transformation based on the estimated outline. We compared the changes in recognition rates of OCR before and after applying the proposed algorithm. The recognition rate of the distortion corrected signboard images is 29.63% and 21.9% higher at the character and the text unit than those of the original images.

Design of Block-based Image Descriptor using Local Color and Texture (지역 칼라와 질감을 활용한 블록 기반 영상 검색 기술자 설계)

  • Park, Sung-Hyun;Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.12 no.4
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    • pp.33-38
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    • 2013
  • Image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes an efficient image descriptor which uses a local color and texture in the non-overlapped block images. To evaluate the performance of the proposed method, we assessed the retrieval efficiency in terms of ANMRR with common image dataset. The experimental trials revealed that the proposed algorithm exhibited a significant improvement in ANMRR, compared to Dominant Color Descriptor and Edge Histogram Descriptor.

Partial Discharge Signal Denoising using Adaptive Translation Invariant Wavelet Transform-Online Measurement

  • Maheswari, R.V.;Subburaj, P.;Vigneshwaran, B.;Iruthayarajan, M. Willjuice
    • Journal of Electrical Engineering and Technology
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    • v.9 no.2
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    • pp.695-706
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    • 2014
  • Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.

Fine Registration between Very High Resolution Satellite Images Using Registration Noise Distribution (등록오차 분포특성을 이용한 고해상도 위성영상 간 정밀 등록)

  • Han, Youkyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.3
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    • pp.125-132
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    • 2017
  • Even after applying an image registration, Very High Resolution (VHR) multi-temporal images acquired from different optical satellite sensors such as IKONOS, QuickBird, and Kompsat-2 show a local misalignment due to dissimilarities in sensor properties and acquisition conditions. As the local misalignment, also referred to as Registration Noise (RN), is likely to have a negative impact on multi-temporal information extraction, detecting and reducing the RN can improve the multi-temporal image processing performance. In this paper, an approach to fine registration between VHR multi-temporal images by considering local distribution of RN is proposed. Since the dominant RN mainly exists along boundaries of objects, we use edge information in high frequency regions to identify it. In order to validate the proposed approach, datasets are built from VHR multi-temporal images acquired by optical satellite sensors. Both qualitative and quantitative assessments confirm the effectiveness of the proposed RN-based fine registration approach compared to the manual registration.