In this program we calculate the sum of the incident and scattered fields in a 90 degree conducting wedge by using the analytic and Image theotem method
標(biāo)簽： conducting calculate the scattered
上傳時(shí)間： 2014-10-27
上傳用戶：lizhen9880
The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.
標(biāo)簽： present modalities existence different
上傳時(shí)間： 2017-04-03
上傳用戶：qunquan
-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. Mutual Information is the similarity measure used in this case for optimizing the two images. This method requires estimating joint histogram of the two images. The fusion of images is the process of combining two or more images into a single image retaining important features from each. The Discrete Wavelet Transform (DWT) has become an attractive tool for fusing multimodal images. In this work it has been used to segment the features of the input images to produce a region map. Features of each region are calculated and a region based approach is used to fuse the images in the wavelet domain.
標(biāo)簽： present modalities existence different
上傳時(shí)間： 2014-03-04
上傳用戶：15736969615
In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements. Image registration is the process of transforming the different sets of data into one coordinate system. To be precise it involves finding transformations that relate spatial information conveyed in one image to that in another or in physical space. Image registration is performed on a series of at least two images, where one of these images is the reference image to which all the others will be registered. The other images are referred to as target images.
標(biāo)簽： different computer acquired sampling
上傳時(shí)間： 2013-12-28
上傳用戶：來茴
The purpose of this study is to compare between the to methods which is JPEG and JPEG2000 that are using in lossless image compression .
標(biāo)簽： JPEG purpose compare between
上傳時(shí)間： 2014-01-15
上傳用戶：cccole0605
pHash is an implementation of various perceptual hashing algorithms. A perceptual hash is a fingerprint of an audio, video, or image file that is mathematically based on the audio or visual content contained within. Unlike cryptographic hash functions that rely on the avalanche effect of small changes in input leading to drastic changes in the output, perceptual hashes are "close" to one another if the inputs are visually or auditorily similar. As a result, perceptual hashes must also be robust enough to take into account transformations that could have been performed on the input.
標(biāo)簽： perceptual implementation algorithms fingerpr
上傳時(shí)間： 2013-12-08
上傳用戶：星仔
This project features a complete JPEG Hardware Compressor (standard Baseline DCT, JFIF header) with 2:1:1 subsampling, able to compress at a rate of up to 24 images per second (on XC2V1000-4 @ 40 MHz with resolution 352x288). Image resolution is not limited. It takes an RGB input (row-wise) and outputs to a memory the compressed JPEG image. Its quality is comparable to software solutions.
標(biāo)簽： Compressor Hardware Baseline features
上傳時(shí)間： 2017-04-21
上傳用戶：wyc199288
Face Recognition Library ======================== Advanced face recognition DLL using two functions : Train and Recognize. Uses neural net back propogation alogorithm with more AI tools added for imaging optimization. Library works great even for a low resolution web cam image and requires the user to align to a mirror frame on screen. Complete Source Code with Video capture and feature extraction kit for Registered Users. Please register here for only $299 with Source Code : http://www.research-lab.com/facerecognitionorder.htm (c) www.research-lab.com
標(biāo)簽： Recognition recognition Advanced Library
上傳時(shí)間： 2017-04-25
上傳用戶：784533221
附件是一份S3C2410的原廠BSP源碼，可以直接通過TORNADO環(huán)境編譯生成BOOTROM和VXWORKS IMAGE，已經(jīng)通過實(shí)驗(yàn)驗(yàn)證，希望能對(duì)BSP移植者有幫助~~~
上傳時(shí)間： 2014-01-02
上傳用戶：ruan2570406
Circular hough transform for eyedetection and precise eyes location. it is a very good code that works on both grayscale and jpg image.
標(biāo)簽： eyedetection transform Circular location
上傳時(shí)間： 2014-01-25
上傳用戶：yiwen213
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