• Title/Summary/Keyword: Histogram matching

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Relative Radiometric Normalization of Hyperion Hyperspectral Images Through Automatic Extraction of Pseudo-Invariant Features for Change Detection (자동 PIF 추출을 통한 Hyperion 초분광영상의 상대 방사정규화 - 변화탐지를 목적으로)

  • Kim, Dae-Sung;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.2
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    • pp.129-137
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    • 2008
  • This study focuses on the radiometric normalization, which is one of the pre-processing steps to apply the change detection technique fur hyperspectral images. The PIFs which had radiometric consistency under the time interval were automatically extracted by applying spectral angle, and used as sample pixels for linear regression of the radiometric normalization. We also dealt with the problem about the number of PIFs for linear regression with iteratively quantitative methods. The results were assessed in comparison with image regression, histogram matching, and FLAASH. In conclusion, we show that linear regression method with PIFs can carry out the efficient result for radiometric normalization.

Automatic Registration between Multiple IR Images Using Simple Pre-processing Method and Modified Local Features Extraction Algorithm (단순 전처리 방법과 수정된 지역적 피쳐 추출기법을 이용한 다중 적외선영상 자동 기하보정)

  • Kim, Dae Sung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.6
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    • pp.485-494
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    • 2017
  • This study focuses on automatic image registration between multiple IR images using simple preprocessing method and modified local feature extraction algorithm. The input images were preprocessed by using the median and absolute value after histogram equalization, and it could be effectively applied to reduce the brightness difference value between images by applying the similarity of extracted features to the concept of angle instead of distance. The results were evaluated using visual and inverse RMSE methods. The features that could not be achieved by the existing local feature extraction technique showed high image matching reliability and application convenience. It is expected that this method can be used as one of the automatic registration methods between multi-sensor images under specific conditions.

Implementation of an Efficient Wavelet Based Audio Data Retrieval System (효율적인 웨이블렛 기반 오디오 데이터 검색 시스템 구현)

  • 이배호;조용춘;김광희
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.1
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    • pp.82-88
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    • 2002
  • In this paper, we proposed a audio indexing method that is used wavelet transform for audio data retrieval. It is difficult for audio data to make a efficient audio data index because of its own particular properties, such as requirement of large storage, real time to transfer and wide bandwidth. An audio data in del using wavelet transform make it possible to index and retrieval by using the particular wavelet transform properties. Our proposed indexing method doesn't separate data to several blocks. Therefore we use both high-pass and low-pass parts of last level coefficient of wavelet transform. Audio data indexing is made by applying the string matching algorithm to high-pass part and zero-crossing histogram to low-pass part. These are transformed to the continued strings, Through this method, we described a retrieval efficiency. The retrieval method is done by comparing the database index string to the query string and then data of minimum values is chosen to the result. Our simulation decided proper comparative coefficient and made known changing of retrieval efficiency versus audio data length. The results show that the proposed method improves retrieval efficiency compared to conventional method.

Detection Method of Human Face, Facial Components and Rotation Angle Using Color Value and Partial Template (컬러정보와 부분 템플릿을 이용한 얼굴영역, 요소 및 회전각 검출)

  • Lee, Mi-Ae;Park, Ki-Soo
    • The KIPS Transactions:PartB
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    • v.10B no.4
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    • pp.465-472
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    • 2003
  • For an effective pre-treatment process of a face input image, it is necessary to detect each of face components, calculate the face area, and estimate the rotary angle of the face. A proposed method of this study can estimate an robust result under such renditions as some different levels of illumination, variable fate sizes, fate rotation angels, and background color similar to skin color of the face. The first step of the proposed method detects the estimated face area that can be calculated by both adapted skin color Information of the band-wide HSV color coordinate converted from RGB coordinate, and skin color Information using histogram. Using the results of the former processes, we can detect a lip area within an estimated face area. After estimating a rotary angle slope of the lip area along the X axis, the method determines the face shape based on face information. After detecting eyes in face area by matching a partial template which is made with both eyes, we can estimate Y axis rotary angle by calculating the eye´s locations in three dimensional space in the reference of the face area. As a result of the experiment on various face images, the effectuality of proposed algorithm was verified.

Automatic Phonetic Segmentation of Korean Speech Signal Using Phonetic-acoustic Transition Information (음소 음향학적 변화 정보를 이용한 한국어 음성신호의 자동 음소 분할)

  • 박창목;왕지남
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.8
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    • pp.24-30
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    • 2001
  • This article is concerned with automatic segmentation for Korean speech signals. All kinds of transition cases of phonetic units are classified into 3 types and different strategies for each type are applied. The type 1 is the discrimination of silence, voiced-speech and unvoiced-speech. The histogram analysis of each indicators which consists of wavelet coefficients and SVF (Spectral Variation Function) in wavelet coefficients are used for type 1 segmentation. The type 2 is the discrimination of adjacent vowels. The vowel transition cases can be characterized by spectrogram. Given phonetic transcription and transition pattern spectrogram, the speech signal, having consecutive vowels, are automatically segmented by the template matching. The type 3 is the discrimination of vowel and voiced-consonants. The smoothed short-time RMS energy of Wavelet low pass component and SVF in cepstral coefficients are adopted for type 3 segmentation. The experiment is performed for 342 words utterance set. The speech data are gathered from 6 speakers. The result shows the validity of the method.

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Technique of Seam-Line Extraction for Automatic Image Mosaic Generation (자동 모자이크 영상제작을 위한 접합선 추출기법에 관한 연구)

  • Song, Nak-Hyeon;Lee, Sung-Hun;Oh, Kum-Hui;Cho, Woo-Sug
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.1
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    • pp.47-53
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    • 2007
  • Satellite image mosaicking is essential for image interpretation and analysis especially for a large area such as the Korean Peninsula. This paper proposed the technique of automatic seam-line extraction and the method of creating image mosaic in automated fashion. The seam-line to minimize artificial discontinuity was extracted using Minimum Absolute Gray Difference Sum algorithm with constraint condition on search-area width and Canny Edge Detection algorithm. To maintain the radiometric balance among images acquired at different time epochs, we utilized Match Cumulative Frequency method. Experimental results showed that edge detection algorithm extracted the seam-lines significantly well along linear features such as roads and rivers.

Real Time Lip Reading System Implementation in Embedded Environment (임베디드 환경에서의 실시간 립리딩 시스템 구현)

  • Kim, Young-Un;Kang, Sun-Kyung;Jung, Sung-Tae
    • The KIPS Transactions:PartB
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    • v.17B no.3
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    • pp.227-232
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    • 2010
  • This paper proposes the real time lip reading method in the embedded environment. The embedded environment has the limited sources to use compared to existing PC environment, so it is hard to drive the lip reading system with existing PC environment in the embedded environment in real time. To solve the problem, this paper suggests detection methods of lip region, feature extraction of lips, and awareness methods of phonetic words suitable to the embedded environment. First, it detects the face region by using face color information to find out the accurate lip region and then detects the exact lip region by finding the position of both eyes from the detected face region and using the geometric relations. To detect strong features of lighting variables by the changing surroundings, histogram matching, lip folding, and RASTA filter were applied, and the properties extracted by using the principal component analysis(PCA) were used for recognition. The result of the test has shown the processing speed between 1.15 and 2.35 sec. according to vocalizations in the embedded environment of CPU 806Mhz, RAM 128MB specifications and obtained 77% of recognition as 139 among 180 words were recognized.

Multi-temporal Landsat ETM+ Mosaic Method for Generating Land Cover Map over the Korean Peninsula (한반도 토지피복도 제작을 위한 다시기 Landsat ETM+ 영상의 정합 방법)

  • Kim, Sun-Hwa;Kang, Sung-Jin;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.87-98
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    • 2010
  • For generating accurate land cover map over the whole Korean Peninsula, post-mosaic classification method is desirable in large area where multiple image data sets are used. We try to derive an optimal mosaic method of multi-temporal Landsat ETM+ scenes for the land cover classification over the Korea Peninsula. Total 65 Landsat ETM+ scenes were acquired, which were taken in 2000 and 2001. To reduce radiometric difference between adjacent Landsat ETM+ scenes, we apply three relative radiometric correction methods (histogram matching, 1st-regression method referenced center image, and 1st-regression method at each Landsat ETM+ path). After the relative correction, we generated three mosaic images for three seasons of leaf-off, transplanting, leaf-on season. For comparison, three mosaic images were compared by the mean absolute difference and computer classification accuracy. The results show that the mosaic image using 1st-regression method at each path show the best correction results and highest classification accuracy. Additionally, the mosaic image acquired during leaf-on season show the higher radiance variance between adjacent images than other season.

Stream flow estimation in small to large size streams using Sentinel-1 Synthetic Aperture Radar (SAR) data in Han River Basin, Korea

  • Ahmad, Waqas;Kim, Dongkyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.152-152
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    • 2019
  • This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

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A Study on Rotational Alignment Algorithm for Improving Character Recognition (문자 인식 향상을 위한 회전 정렬 알고리즘에 관한 연구)

  • Jin, Go-Whan
    • Journal of the Korea Convergence Society
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    • v.10 no.11
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    • pp.79-84
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    • 2019
  • Video image based technology is being used in various fields with continuous development. The demand for vision system technology that analyzes and discriminates image objects acquired through cameras is rapidly increasing. Image processing is one of the core technologies of vision systems, and is used for defect inspection in the semiconductor manufacturing field, object recognition inspection such as the number of tire surfaces and symbols. In addition, research into license plate recognition is ongoing, and it is necessary to recognize objects quickly and accurately. In this paper, propose a recognition model through the rotational alignment of objects after checking the angle value of the tilt of the object in the input video image for the recognition of inclined objects such as numbers or symbols marked on the surface. The proposed model can perform object recognition of the rotationally sorted image after extracting the object region and calculating the angle of the object based on the contour algorithm. The proposed model extracts the object region based on the contour algorithm, calculates the angle of the object, and then performs object recognition on the rotationally aligned image. In future research, it is necessary to study template matching through machine learning.