自己編寫的一個(gè)簡單的matlab程序,實(shí)現(xiàn)圖像直方圖的均衡化及規(guī)定化處理.image histogram equalization,histogram matching(specification).
上傳時(shí)間: 2014-11-11
上傳用戶:klin3139
This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings in monocular aerial images. With the suggested method building outlines can be detected faster than the mobile robot can explore the area by itself, giving the robot an ability to “see” around corners. At the same time, the approach can compensate for the absence of elevation data in segmentation of aerial images. Our experiments demonstrate that ground-level semantic information (wall estimates) allows to focus the segmentation of the aerial image to find buildings and produce a ground-level semantic map that covers a larger area than can be built using the onboard sensors.
標(biāo)簽: simultaneously difficulties limitation addresses
上傳時(shí)間: 2014-06-11
上傳用戶:waitingfy
Semantic analysis of multimedia content is an on going research area that has gained a lot of attention over the last few years. Additionally, machine learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach to semantic adaptation of neural network classifiers in multimedia framework. It is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a knowledge base. Improved image segmentation results are obtained, which are used for adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content.
標(biāo)簽: multimedia Semantic analysis research
上傳時(shí)間: 2016-11-24
上傳用戶:蟲蟲蟲蟲蟲蟲
We propose a technique that allows a person to design a new photograph with substantially less effort. This paper presents a method that generates a composite image when a user types in nouns, such as “boat” and “sand.” The artist can optionally design an intended image by specifying other constraints. Our algorithm formulates the constraints as queries to search an automatically annotated image database. The desired photograph, not a collage, is then synthesized using graph-cut optimization, optionally allowing for further user interaction to edit or choose among alternative generated photos. An implementation of our approach, shown in the associated video, demonstrates our contributions of (1) a method for creating specific images with minimal human effort, and (2) a combined algorithm for automatically building an image library with semantic annotations from any photo collection.
標(biāo)簽: substantially photograph technique propose
上傳時(shí)間: 2016-11-24
上傳用戶:三人用菜
Range imaging offers an inexpensive and accurate means for digitizing the shape of three-dimensional objects. Because most objects self occlude, no single range image suffices to describe the entire object. We present a method for combining a collection of range images into a single polygonal mesh that completely describes an object to the extent that it is visible from the outside.
標(biāo)簽: three-dimensiona inexpensive digitizing accurate
上傳時(shí)間: 2016-11-29
上傳用戶:yxgi5
掌握在uC/OS-II 操作系統(tǒng)下使用ZLG/GUI的基本方法。 1. 啟動(dòng) ADS 1.2,使用 ARM Executable Image for UCOSII(for lpc22xx)工程模板建立一 個(gè)工程 gui_ucos,工程存儲(chǔ)在 uCOS-II 目錄下。 說明:在 uCOS-II 目錄下要保存有 uCOS-II 的移植代碼和內(nèi)核源代碼。 2. 建立 C 源文件 Test .c,編寫實(shí)驗(yàn)程序,保存到 gui_ucos\src 目錄下,然后添加到工程 的 user組中。 3. 復(fù)制 ZLG/GUI 文件。把 ZLG_GUI 整個(gè)目錄及文件復(fù)制到 gui_ucos\SRC 目錄下。 4. 添加 ZLG/GUI 文件。在工程管理窗口中新建一個(gè)組 ZLG/GUI,然后在這個(gè)組內(nèi)添 加 gui_ucos\SRC\ZLG_GUI下的所有 C 源程序文件和 GUI_CONFIG.H配置文件。 5. 新建驅(qū)動(dòng)程序,在工程管理窗口中新建一個(gè)組 lcd_drive,并將驅(qū)動(dòng)程序添加到工程 的 lcd_drive組中。驅(qū)動(dòng)程序文件名比如:LCDDRIVE.c、LCDDRIVE.H,可以保存 在 gui_ucos\SRC 目錄下。 6. 修改 CONFIG.H,增加包含 LCDDRIVE.H 頭文件和 ZLG/GUI 的所有頭文件,如程 序清單 1.3 所示。
上傳時(shí)間: 2013-12-21
上傳用戶:wyc199288
將SQLSERVER記錄還原生成Insert的SQL語句,方便生成數(shù)據(jù)庫安裝記錄,備份重要數(shù)據(jù), 支持字段多,但暫時(shí)不支持image類字段
標(biāo)簽: SQLSERVER Insert SQL 記錄
上傳時(shí)間: 2014-01-27
上傳用戶:清風(fēng)冷雨
15篇光流配準(zhǔn)經(jīng)典文獻(xiàn),目錄如下: 1、A Local Approach for Robust Optical Flow Estimation under Varying 2、A New Method for Computing Optical Flow 3、Accuracy vs. Efficiency Trade-offs in Optical Flow Algorithms 4、all about direct methods 5、An Introduction to OpenCV and Optical Flow 6、Bayesian Real-time Optical Flow 7、Color Optical Flow 8、Computation of Smooth Optical Flow in a Feedback Connected Analog Network 9、Computing optical flow with physical models of brightness Variation 10、Dense estimation and object-based segmentation of the optical flow with robust techniques 11、Example Goal Standard methods Our solution Optical flow under 12、Exploiting Discontinuities in Optical Flow 13、Optical flow for Validating Medical Image Registration 14、Tutorial Computing 2D and 3D Optical Flow.pdf 15、The computation of optical flow
標(biāo)簽: 光流
上傳時(shí)間: 2014-11-21
上傳用戶:fanboynet
AR6001 WLAN Driver for SDIO installation Read Me March 26,2007 (based on k14 fw1.1) Windows CE Embedded CE 6.0 driver installation. 1. Unzip the installation file onto your system (called installation directory below) 2. Create an OS design or open an existing OS design in Platform Builder 6.0. a. The OS must support the SD bus driver and have an SD Host Controller driver (add these from Catalog Items). b. Run image size should be set to allow greater than 32MB. 3. a. From the Project menu select Add Existing Subproject... b. select AR6K_DRV.pbxml c. select open This should create a subproject within your OS Design project for the AR6K_DRV driver. 4. Build the solution.
標(biāo)簽: installation Windows Driver March
上傳時(shí)間: 2014-09-06
上傳用戶:yuzsu
(1)ICCV1999 Object Recognition from Local Scale-Invariant Features.pdf提出(2)IJCV2004 Distinctive image features from scale invariant keypoints.pdf總結(jié)(3)CVPR2004 PCA-SIFT:A More Distinctive Representation for Local Image Descriptors.pdf加PCA降維
標(biāo)簽: Scale-Invariant Distinctive Recognition Features
上傳時(shí)間: 2013-12-27
上傳用戶:yepeng139
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