一级黄色片免费播放|中国黄色视频播放片|日本三级a|可以直接考播黄片影视免费一级毛片

高級搜索

留言板

尊敬的讀者、作者、審稿人, 關于本刊的投稿、審稿、編輯和出版的任何問題, 您可以本頁添加留言。我們將盡快給您答復。謝謝您的支持!

姓名
郵箱
手機號碼
標題
留言內(nèi)容
驗證碼

融合時空上下文信息的胸環(huán)靶著彈檢測算法

王洪玉,  程楊

王洪玉, 程楊. 融合時空上下文信息的胸環(huán)靶著彈檢測算法[J]. 電子與信息學報, 2020, 42(8): 1959-1967. doi: 10.11999/JEIT190585
引用本文: 王洪玉, 程楊. 融合時空上下文信息的胸環(huán)靶著彈檢測算法[J]. 電子與信息學報, 2020, 42(8): 1959-1967. doi: 10.11999/JEIT190585
Hongyu WANG, Yang CHENG. Detection Algorithm of Chest Bitmap Based on Spatio-temporal Context Information[J]. Journal of Electronics & Information Technology, 2020, 42(8): 1959-1967. doi: 10.11999/JEIT190585
Citation: Hongyu WANG, Yang CHENG. Detection Algorithm of Chest Bitmap Based on Spatio-temporal Context Information[J]. Journal of Electronics & Information Technology, 2020, 42(8): 1959-1967. doi: 10.11999/JEIT190585

融合時空上下文信息的胸環(huán)靶著彈檢測算法

doi: 10.11999/JEIT190585 cstr: 32379.14.JEIT190585

  • 大連理工大學信息與通信工程學院 大連 116024

基金項目: 國家自然科學基金(61671103)
詳細信息
    作者簡介:

    王洪玉：男，1968年生，教授，博士生導師，研究方向為圖像處理、計算機視覺

    程楊：女，1995年生，碩士生，研究方向為圖像處理、計算機視覺

    通訊作者:

    王洪玉　whyu@dlut.edu.cn

  • 中圖分類號: TN911.73; TP391.41

Detection Algorithm of Chest Bitmap Based on Spatio-temporal Context Information

  • School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China

Funds: The National Natural Science Foundation of China (61671103)
  • 摘要:

    為減小光照不均與隨機抖動對胸環(huán)靶著彈檢測精度的影響，該文提出一種融合時空上下文信息的胸環(huán)靶著彈檢測算法。利用目標及其鄰域的空間上下文信息進行光照均衡化，并提取胸環(huán)靶序列間時域運動上下文信息進行抖動校正。為提高胸環(huán)靶圖像的穩(wěn)定性，該算法提出多參數(shù)融合方法對抖動校正后的序列圖像進行像素級融合。接著進行彈孔區(qū)域粗提取、能量篩選與重疊彈孔判別，獲得彈孔位置分布。采用在部隊靶場實地采集的圖像進行實驗，驗證了該算法可以有效抑制光照不均與隨機抖動帶來的噪聲影響，具有較好的彈孔提取能力。

    Abstract:

    A detection algorithm based on spatio-temporal context information is proposed to reduce the influence of non-uniform illumination and random jitter on the accuracy of target hole detection. The light equalization is carried out by using the spatial context information of target and its neighborhood, and the temporal motion context information between chest bitmap sequences is extracted for dithering correction. In order to improve the stability of chest bitmaps, a multi-parameter fusion method is proposed to perform pixel-level fusion of jitter corrected sequence images. Then, rough extraction of bullet hole area, energy screening and overlapping bullet holes discrimination are carried out to obtain the location distribution of bullet holes. The experimental results show that the algorithm can effectively suppress the noise caused by non-uniform illumination and random jitter, and has great ability of bullet hole extraction.

    • HTML全文

  • 圖  1  融合時空上下文信息的檢測算法流程圖

    圖  2  待檢測圖像采集過程

    圖  3  同態(tài)濾波結果圖

    圖  4  圖像跟蹤與配準示意圖

    圖  5  多參數(shù)圖像融合

    圖  6  彈孔分割圖像

    圖  7  重疊彈孔示意圖

    圖  8  相機與胸環(huán)靶位置分布圖

    圖  9  部分實驗圖像

    圖  10  漏檢彈孔圖

    圖  11  正午時段圖像檢測結果

    圖  12  下午時段圖像檢測結果

    圖  13  黃昏時段圖像檢測結果

    圖  14  彈孔中心坐標分布圖

    表  1  IQA參數(shù)比較

    ${\mu _1}$(mean)${\mu _2}$(std)${\mu _3}$(grad)SSEQ
    0.10.40.549.7565
    0.20.30.550.7473
    0.30.20.550.5672
    0.40.10.549.4026
    0.10.30.649.2834
    0.20.20.650.0364
    0.30.10.649.9368
    0.10.20.749.2470
    0.20.10.749.3499
    0.10.10.848.9924
    下載: 導出CSV

    表  2  算法檢測精度

    彈孔總數(shù)檢測總數(shù)FNRFPR圖像尺寸累計時間(s)
    39370.07690.02701280$ \times $96023.031
    下載: 導出CSV

    表  3  彈孔中心坐標位置偏差與檢測效率

    序號真值檢測結果$(|\Delta x|,|\Delta y|)$$\sqrt {\Delta {x^2} + \Delta {y^2}} $檢測效率(s)
    1(206,725)(206.50,725.00)(0.50,0)0.500.7413
    2(460,297)(459.63,297.50)(0.37,0.50)0.620.7744
    3(267,541)(266.35,542.24)(0.65,1.24)1.400.8000
    4(436,456)(436.77,457.13)(0.77,1.13)1.370.7711
    5(733,626)(733.00,626.49)(0,0.49)0.490.7656
    6(685,891)(686.50,888.50)(1.50,2.50)2.920.7711
    7(797,915)(796.50,915.50)(0.50,0.50)0.710.7586
    8(573,821)(573.00,819.50)(0,1.50)1.500.7843
    9(700,758)(699.00,758.00)(1.00,0)1.000.7946
    10(760,711)(760.13,710.32)(0.13,0.68)0.690.8425
    下載: 導出CSV
  • 苑瑋琦, 李夢祺. 基于視覺檢測的胸環(huán)靶自動報靶系統(tǒng)研究[J]. 計算機技術與發(fā)展, 2019, 29(2): 147–151. doi: 10.3969/j.issn.1673-629X.2019.02.031

    YUAN Weiqi and LI Mengqi. Research on target of automatic scoring system based on visual inspection[J]. Computer Technology and Development, 2019, 29(2): 147–151. doi: 10.3969/j.issn.1673-629X.2019.02.031
    羅杰, 張之明. 基于圖像處理技術自動報靶系統(tǒng)綜述[J]. 激光雜志, 2016, 37(7): 1–6. doi: 10.14016/j.cnki.jgzz.2016.07.001

    LUO Jie and ZHANG Zhiming. Survey on automatic target-scoring system based on image processing technology[J]. Laser Journal, 2016, 37(7): 1–6. doi: 10.14016/j.cnki.jgzz.2016.07.001
    尹乾. 基于圖像處理技術的自動報靶系統(tǒng)研究[D]. [碩士論文], 重慶大學, 2017: 37–45.

    YIN Qian. Study on automatic target scoring based on image processing technology[D]. [Master dissertation], Chongqing University, 2017: 37–45.
    WIDAYAKA P D, KUSUMA H, and ATTAMIMI M. Automatic shooting scoring system based on image processing[J]. Journal of Physics: Conference Series, 2019, 1201: 012047. doi: 10.1088/1742-6596/1201/1/012047
    余梓. 基于圖像處理技術的彈孔定位系統(tǒng)研究[D]. [碩士論文], 哈爾濱理工大學, 2016: 27–40.

    YU Zi. Study on bullet hole positioning system based on image processing technology[D]. [Master dissertation], Harbin University of Science and Technology, 2016: 27–40.
    周友行, 周健, 鄧渝波, 等. 基于邊緣特征與HSI色彩特征的胸環(huán)靶彈孔識別[J]. 計算機工程與應用, 2015, 51(24): 190–194. doi: 10.3778/j.issn.1002-8331.1312-0221

    ZHOU Youhang, ZHOU Jian, DENG Yubo, et al. Chest bitmap bullet identification based on edge feature and HSI color feature[J]. Computer Engineering and Applications, 2015, 51(24): 190–194. doi: 10.3778/j.issn.1002-8331.1312-0221
    徐建強, 陸耀. 一種基于加權時空上下文的魯棒視覺跟蹤算法[J]. 自動化學報, 2015, 41(11): 1901–1912. doi: 10.16383/j.aas.2015.c150073

    XU Jianqiang and LU Yao. Robust visual tracking via weighted spatio-temporal context learning[J]. Acta Automatica Sinica, 2015, 41(11): 1901–1912. doi: 10.16383/j.aas.2015.c150073
    程新. 基于同態(tài)濾波的圖像增強算法研究[D]. [碩士論文], 西安郵電大學, 2016: 33–40.

    CHENG Xin. Image enhancement algorithm based on homomorphic filtering[D]. [Master dissertation], Xi’an University of Posts & Telecommunications, 2016: 33–40.
    TIAN Qichong and COHEN L D. Global and local contrast adaptive enhancement for non-uniform illumination color images[C]. 2017 IEEE International Conference on Computer Vision Workshop (ICCVW), Venice, Italy, 2017: 3023–3030. doi: 10.1109/ICCVW.2017.357.
    魏閃閃, 謝巍, 賀志強. 數(shù)字視頻穩(wěn)像技術綜述[J]. 計算機研究與發(fā)展, 2017, 54(9): 2044–2058. doi: 10.7544/issn1000-1239.2017.20160078

    WEI Shanshan, XIE Wei, and HE Zhiqiang. Digital video stabilization techniques: A survey[J]. Journal of Computer Research and Development, 2017, 54(9): 2044–2058. doi: 10.7544/issn1000-1239.2017.20160078
    胡瑞卿, 田杰榮. 基于光流法的運動目標檢測算法研究[J]. 電子世界, 2019(5): 58–61. doi: 10.19353/j.cnki.dzsj.2019.05.031

    HU Ruiqing and TIAN Jierong. Research on moving target detection algorithm based on optical flow method[J]. Electronics World, 2019(5): 58–61. doi: 10.19353/j.cnki.dzsj.2019.05.031
    田偉, 柏方超. 基于特征點的KLT實時目標跟蹤算法實現(xiàn)[J]. 光電技術應用, 2019, 34(1): 31–34. doi: 10.3969/j.issn.1673-1255.2019.01.007

    TIAN Wei and BAI Fangchao. Implementation of KLT target tracking algorithm feature point-based[J]. Electro-Optic Technology Application, 2019, 34(1): 31–34. doi: 10.3969/j.issn.1673-1255.2019.01.007
    王喆. 多聚焦圖像像素級融合算法研究[D]. [碩士論文], 鄭州大學, 2018: 15–30.

    WANG Zhe. Research on pixel-level fusion algorithms for multi-focus image[D]. [Master dissertation], Zhengzhou University, 2018: 15–30.
    GOH T Y, BASAH S N, YAZID H, et al. Performance analysis of image thresholding: Otsu technique[J]. Measurement, 2018, 114: 298–307. doi: 10.1016/j.measurement.2017.09.052
    LIU Lixiong, LIU Bao, HUANG Hua, et al. No-reference image quality assessment based on spatial and spectral entropies[J]. Signal Processing: Image Communication, 2014, 29(8): 856–863. doi: 10.1016/j.image.2014.06.006
  • 加載中
圖(14) / 表(3)
計量
  • 文章訪問數(shù):  2662
  • HTML全文瀏覽量:  1189
  • PDF下載量:  48
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2019-08-02
  • 修回日期:  2020-02-13
  • 網(wǎng)絡出版日期:  2020-03-25
  • 刊出日期:  2020-08-18

目錄

    /

    返回文章
    返回