智能視覺物聯(lián)網(wǎng)中視覺特性的提取及視覺標簽的建立
發(fā)布時間：2019-06-21 02:41
【摘要】：智能視覺物聯(lián)網(wǎng)(IVIOT),即具有視覺感知功能的物聯(lián)網(wǎng)。它通常由四個部分組成:視覺傳感器、視覺信息傳輸、視覺信息處理和物聯(lián)網(wǎng)應(yīng)用。智能視覺物聯(lián)網(wǎng)是物聯(lián)網(wǎng)的升級,它將圖像傳感器傳來的圖像,利用圖像處理技術(shù)或計算機視覺技術(shù)等,進行智能化識別、定位、跟蹤,便于我們對人、車、物進行智能化管理。智能視覺物聯(lián)網(wǎng)中最重要的一個核心技術(shù)就是視覺標簽技術(shù)。它可以將視頻或圖像中的內(nèi)容進行識別、理解和分類,并為其"貼標簽",并將被識別對象所對應(yīng)的標簽信息內(nèi)容顯示出來。本文根據(jù)課題需要,設(shè)計并實現(xiàn)了一套基于人、車、物的視覺標簽系統(tǒng)。系統(tǒng)主要包括人物識別模塊,車輛識別模塊,物體識別模塊。在這個系統(tǒng)中,可以根據(jù)用戶需求,選擇一幅圖片,系統(tǒng)會自動識別該圖片中的內(nèi)容,并顯示與之相關(guān)的其它圖片以及其信息標簽。在人物識別模塊,本文基于人臉識別技術(shù),采用主成分分析(Principal Component Analysis,PCA)算法和支持向量機(Support Vector Machine,SVM)算法相結(jié)合的方法進行人臉識別。首先利用PCA算法進行特征提取和降維,再利用SVM算法進行分類和識別。在車輛識別模塊,本文采用基于顏色的車牌識別算法,對智能視覺物聯(lián)網(wǎng)中獲得的圖像中的車輛,進行車牌定位、車牌校正、字符分割、字符識別等處理,最終識別出車牌號碼。在物體識別模塊,本文采用基于卷積神經(jīng)網(wǎng)絡(luò)的物體識別方法,完成了同類物體的識別(本文以水杯為例)。最后,本文將三個模塊整合到一個系統(tǒng)中,使人、車、物一一對應(yīng),開發(fā)了一套具有視覺標簽功能的人、車、物智能識別系統(tǒng)。實驗結(jié)果表明,該系統(tǒng)具有很好的性能,能夠滿足用戶的基礎(chǔ)需求。
[Abstract]:Intelligent visual Internet of things (IVIOT),) is the Internet of things with visual perception function. It usually consists of four parts: visual sensor, visual information transmission, visual information processing and Internet of things application. Intelligent vision Internet of things is an upgrade of the Internet of things. It uses image processing technology or computer vision technology to intelligently identify, locate and track the image from the image sensor, which is convenient for us to manage people, cars and things intelligently. One of the most important core technologies in the intelligent visual Internet of things is visual tagging technology. It can identify, understand and classify the content of video or image, and "label" it, and display the content of label information corresponding to the identified object. According to the needs of the project, this paper designs and implements a set of visual label system based on human, car and object. The system mainly includes character recognition module, vehicle recognition module and object recognition module. In this system, a picture can be selected according to the needs of the user, and the system automatically recognizes the contents of the picture and displays other pictures and its information labels. In the character recognition module, based on face recognition technology, this paper uses principal component analysis (Principal Component Analysis,PCA) algorithm and support vector machine (Support Vector Machine,SVM) algorithm to carry out face recognition. Firstly, PCA algorithm is used for feature extraction and dimension reduction, and then SVM algorithm is used for classification and recognition. In the vehicle recognition module, this paper uses the color-based license plate recognition algorithm to identify the license plate number of the vehicle in the image obtained from the intelligent visual Internet of things, such as license plate location, license plate correction, character segmentation, character recognition and so on. In the object recognition module, the object recognition method based on convolution neural network is used to complete the recognition of the same kind of object (taking the water cup as an example). Finally, this paper integrates three modules into one system, and develops a set of intelligent recognition system of human, car and thing with visual label function. The experimental results show that the system has good performance and can meet the basic needs of users.
【學(xué)位授予單位】：內(nèi)蒙古大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.4;TN929.5
[Abstract]:Intelligent visual Internet of things (IVIOT),) is the Internet of things with visual perception function. It usually consists of four parts: visual sensor, visual information transmission, visual information processing and Internet of things application. Intelligent vision Internet of things is an upgrade of the Internet of things. It uses image processing technology or computer vision technology to intelligently identify, locate and track the image from the image sensor, which is convenient for us to manage people, cars and things intelligently. One of the most important core technologies in the intelligent visual Internet of things is visual tagging technology. It can identify, understand and classify the content of video or image, and "label" it, and display the content of label information corresponding to the identified object. According to the needs of the project, this paper designs and implements a set of visual label system based on human, car and object. The system mainly includes character recognition module, vehicle recognition module and object recognition module. In this system, a picture can be selected according to the needs of the user, and the system automatically recognizes the contents of the picture and displays other pictures and its information labels. In the character recognition module, based on face recognition technology, this paper uses principal component analysis (Principal Component Analysis,PCA) algorithm and support vector machine (Support Vector Machine,SVM) algorithm to carry out face recognition. Firstly, PCA algorithm is used for feature extraction and dimension reduction, and then SVM algorithm is used for classification and recognition. In the vehicle recognition module, this paper uses the color-based license plate recognition algorithm to identify the license plate number of the vehicle in the image obtained from the intelligent visual Internet of things, such as license plate location, license plate correction, character segmentation, character recognition and so on. In the object recognition module, the object recognition method based on convolution neural network is used to complete the recognition of the same kind of object (taking the water cup as an example). Finally, this paper integrates three modules into one system, and develops a set of intelligent recognition system of human, car and thing with visual label function. The experimental results show that the system has good performance and can meet the basic needs of users.
【學(xué)位授予單位】：內(nèi)蒙古大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.4;TN929.5
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