CN108363970B - 一种鱼种类的识别方法和系统 - Google Patents
一种鱼种类的识别方法和系统 Download PDFInfo
- Publication number
- CN108363970B CN108363970B CN201810105729.3A CN201810105729A CN108363970B CN 108363970 B CN108363970 B CN 108363970B CN 201810105729 A CN201810105729 A CN 201810105729A CN 108363970 B CN108363970 B CN 108363970B
- Authority
- CN
- China
- Prior art keywords
- image
- neural network
- network model
- features
- wavelet neural
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 241000251468 Actinopterygii Species 0.000 title claims abstract description 110
- 238000000034 method Methods 0.000 title claims abstract description 90
- 238000003062 neural network model Methods 0.000 claims abstract description 99
- 239000013598 vector Substances 0.000 claims abstract description 46
- 238000000605 extraction Methods 0.000 claims abstract description 39
- 239000011159 matrix material Substances 0.000 claims description 66
- 210000002569 neuron Anatomy 0.000 claims description 39
- 238000000556 factor analysis Methods 0.000 claims description 33
- 238000013528 artificial neural network Methods 0.000 claims description 24
- 238000012549 training Methods 0.000 claims description 24
- 238000013519 translation Methods 0.000 claims description 16
- 238000003860 storage Methods 0.000 claims description 9
- 238000001914 filtration Methods 0.000 claims description 6
- 238000012847 principal component analysis method Methods 0.000 claims description 4
- 238000004590 computer program Methods 0.000 description 10
- 230000006870 function Effects 0.000 description 10
- 230000008569 process Effects 0.000 description 10
- 238000009826 distribution Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 241001609213 Carassius carassius Species 0.000 description 4
- 239000000284 extract Substances 0.000 description 4
- 230000009467 reduction Effects 0.000 description 4
- 239000000126 substance Substances 0.000 description 4
- 241001014350 Cynoglossus semilaevis Species 0.000 description 3
- 241000252233 Cyprinus carpio Species 0.000 description 3
- 241000252234 Hypophthalmichthys nobilis Species 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 3
- 238000003708 edge detection Methods 0.000 description 3
- 238000000513 principal component analysis Methods 0.000 description 3
- 241000894007 species Species 0.000 description 3
- 201000004569 Blindness Diseases 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 230000000877 morphologic effect Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000003672 processing method Methods 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 241001519451 Abramis brama Species 0.000 description 1
- 238000012935 Averaging Methods 0.000 description 1
- 241000252230 Ctenopharyngodon idella Species 0.000 description 1
- 241000269319 Squalius cephalus Species 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000005284 excitation Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000013505 freshwater Substances 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012886 linear function Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012706 support-vector machine Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/103—Static body considered as a whole, e.g. static pedestrian or occupant recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/048—Activation functions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Multimedia (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Health & Medical Sciences (AREA)
- Computational Linguistics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Biophysics (AREA)
- Molecular Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Biomedical Technology (AREA)
- Evolutionary Biology (AREA)
- Human Computer Interaction (AREA)
- Health & Medical Sciences (AREA)
- Image Analysis (AREA)
Abstract
Description
鱼种类 | 能量均值 | 对比度均值 | 相关均值 | 熵均值 |
半滑舌鳎1 | 0.1559 | 0.5713 | 0.0813 | 2.7106 |
半滑舌鳎2 | 0.8824 | 0.1279 | 1.2676 | 0.4431 |
鲫鱼1 | 0.8041 | 0.5965 | 0.0731 | 0.7645 |
鲫鱼2 | 0.7347 | 0.0062 | 30.1243 | 0.5595 |
鲤鱼1 | 0.9828 | 0.0030 | 53.7906 | 0.0654 |
鲤鱼2 | 0.6533 | 7.4003 | 0.0661 | 1.3942 |
鲢鱼1 | 0.9994 | 0.0062 | 58.7576 | 0.0032 |
鲢鱼2 | 0.7491 | 0.4978 | 0.0664 | 0.8662 |
Claims (3)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810105729.3A CN108363970B (zh) | 2018-02-02 | 2018-02-02 | 一种鱼种类的识别方法和系统 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810105729.3A CN108363970B (zh) | 2018-02-02 | 2018-02-02 | 一种鱼种类的识别方法和系统 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN108363970A CN108363970A (zh) | 2018-08-03 |
CN108363970B true CN108363970B (zh) | 2021-03-23 |
Family
ID=63004338
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810105729.3A Active CN108363970B (zh) | 2018-02-02 | 2018-02-02 | 一种鱼种类的识别方法和系统 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108363970B (zh) |
Families Citing this family (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109275609B (zh) * | 2018-11-14 | 2021-06-01 | 常州大学 | 基于图像处理的常见淡水鱼种类自动识别方法 |
CN109784361A (zh) * | 2018-12-05 | 2019-05-21 | 鲁东大学 | 贝类产品分类识别方法及装置 |
CN109636790B (zh) * | 2018-12-13 | 2021-07-27 | 北京理工大学 | 一种管路结构的识别方法及装置 |
CN109635461B (zh) * | 2018-12-18 | 2022-04-29 | 中国铁建重工集团股份有限公司 | 一种应用随钻参数来自动识别围岩级别的方法和系统 |
CN110321868A (zh) | 2019-07-10 | 2019-10-11 | 杭州睿琪软件有限公司 | 对象识别及显示的方法及系统 |
CN110852376B (zh) * | 2019-11-11 | 2023-05-26 | 杭州睿琪软件有限公司 | 用于识别生物种类的方法及系统 |
CN111127396B (zh) * | 2019-11-21 | 2023-10-27 | 中国农业大学 | 鱼类重量测算方法及装置 |
CN111248169A (zh) * | 2020-01-16 | 2020-06-09 | 苏华 | 一种新型抄网及其数据查询方法、系统 |
CN111406693A (zh) * | 2020-04-23 | 2020-07-14 | 上海海洋大学 | 基于仿生海鳗的海洋牧场渔业资源养护效果评价方法 |
CN111693774A (zh) * | 2020-05-06 | 2020-09-22 | 南方电网科学研究院有限责任公司 | 一种输电网的谐波测量方法和装置 |
CN113109669B (zh) * | 2021-04-12 | 2022-11-25 | 国网陕西省电力公司西安供电公司 | 一种基于行波特征频率的配电网混联线路故障定位方法 |
CN113487728B (zh) * | 2021-07-23 | 2022-02-11 | 中国科学院水生生物研究所 | 一种鱼体模型确定方法及系统 |
CN115051864B (zh) * | 2022-06-21 | 2024-02-27 | 郑州轻工业大学 | 基于pca-mf-wnn的网络安全态势要素提取方法及系统 |
CN115761517B (zh) * | 2023-01-06 | 2023-04-07 | 联通(江苏)产业互联网有限公司 | 一种基于神经网络和物联网的农业场景识别方法 |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102831478A (zh) * | 2012-08-05 | 2012-12-19 | 珠海派诺科技股份有限公司 | 一种基于bp神经网络的地铁能耗综合预测方法 |
CN103077408A (zh) * | 2012-11-13 | 2013-05-01 | 国家海洋局第二海洋研究所 | 基于小波神经网络的海底声纳图像转换为声学底质类别方法 |
CN107423745A (zh) * | 2017-03-27 | 2017-12-01 | 浙江工业大学 | 一种基于神经网络的鱼类活性分类方法 |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102279976A (zh) * | 2011-09-22 | 2011-12-14 | 河南工业大学 | 不同糙米籽粒识别的bp神经网络构建及识别方法 |
-
2018
- 2018-02-02 CN CN201810105729.3A patent/CN108363970B/zh active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102831478A (zh) * | 2012-08-05 | 2012-12-19 | 珠海派诺科技股份有限公司 | 一种基于bp神经网络的地铁能耗综合预测方法 |
CN103077408A (zh) * | 2012-11-13 | 2013-05-01 | 国家海洋局第二海洋研究所 | 基于小波神经网络的海底声纳图像转换为声学底质类别方法 |
CN107423745A (zh) * | 2017-03-27 | 2017-12-01 | 浙江工业大学 | 一种基于神经网络的鱼类活性分类方法 |
Non-Patent Citations (3)
Title |
---|
基于径向基函数的位置预测技术;李智超 等;《微计算机信息》;20121231;第28卷(第10期);第7页 * |
基于时间序列的小波神经网络蔬菜价格预测模型;钱彬彬 等;《洛阳理工学院学报( 自然科学版)》;20161231;第26卷(第4期);第64页和图2 * |
基于机器视觉的淡水鱼品种识别;姚润璐 等;《图像与多媒体》;20171231;第36卷(第24期);摘要和第37-39页 * |
Also Published As
Publication number | Publication date |
---|---|
CN108363970A (zh) | 2018-08-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108363970B (zh) | 一种鱼种类的识别方法和系统 | |
CN108765412A (zh) | 一种带钢表面缺陷分类方法 | |
CN108510499B (zh) | 一种基于模糊集和Otsu的图像阈值分割方法及装置 | |
CN111507426B (zh) | 基于视觉融合特征的无参考图像质量分级评价方法及装置 | |
CN108550145B (zh) | 一种sar图像质量评估方法和装置 | |
Deng et al. | Blind noisy image quality assessment using sub-band kurtosis | |
CN109035196B (zh) | 基于显著性的图像局部模糊检测方法 | |
Smith et al. | Effect of pre-processing on binarization | |
CN114170418B (zh) | 一种以图搜图的汽车线束连接器多特征融合图像检索方法 | |
Niu et al. | Siamese-network-based learning to rank for no-reference 2D and 3D image quality assessment | |
CN109190571B (zh) | 一种放牧绵羊采食典型植物种类的检测识别方法及其装置 | |
CN113610862A (zh) | 一种屏幕内容图像质量评估方法 | |
CN108830829B (zh) | 联合多种边缘检测算子的无参考质量评价算法 | |
Peter et al. | Nonlocal-means image denoising technique using robust M-estimator | |
Feng et al. | A novel saliency detection method for wild animal monitoring images with WMSN | |
Chupraphawan et al. | Deep convolutional neural network with edge feature for image denoising | |
CN113313179A (zh) | 一种基于l2p范数鲁棒最小二乘法的噪声图像分类方法 | |
CN116524269A (zh) | 一种视觉识别检测系统 | |
Jeelani et al. | Content-aware enhancement of images with filamentous structures | |
CN110147824B (zh) | 一种图像的自动分类方法及装置 | |
Vizváry et al. | Image quality detection using the Siamese convolutional neural network | |
Santoso et al. | Hybrid Method and Similarity to Recognize Javanese Keris | |
Lyasheva et al. | Application of image weight models to increase canny contour detector resilience to interference | |
Wei et al. | No reference image quality assessment based on SIFT feature points | |
Bashar | BM3D Image Denoising using Learning-Based Adaptive Hard Thresholding |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
CB03 | Change of inventor or designer information | ||
CB03 | Change of inventor or designer information |
Inventor after: Qu Haiping Inventor after: Zhang Hongyan Inventor before: Qu Haiping Inventor before: Zhang Hongyan Inventor before: Yue Jun Inventor before: Kou Guangjie Inventor before: Zhang Zhiwang Inventor before: Li Zhenbo |
|
GR01 | Patent grant | ||
GR01 | Patent grant | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A method and system for identifying fish species Effective date of registration: 20211216 Granted publication date: 20210323 Pledgee: Yantai financing guarantee Group Co.,Ltd. Pledgor: LUDONG University Registration number: Y2021980015152 |
|
PC01 | Cancellation of the registration of the contract for pledge of patent right | ||
PC01 | Cancellation of the registration of the contract for pledge of patent right |
Date of cancellation: 20220317 Granted publication date: 20210323 Pledgee: Yantai financing guarantee Group Co.,Ltd. Pledgor: LUDONG University Registration number: Y2021980015152 |
|
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20221124 Address after: 100089 No. 258, second floor, building 3, Xisanqi building materials City, Haidian District, Beijing Patentee after: Beijing Zhongke Haixin Technology Co.,Ltd. Address before: 264025 No. 186 Hongqi Middle Road, Zhifu District, Shandong, Yantai Patentee before: LUDONG University |