Image Registration Matching Colors By Using Mosaic Image For Baghdad City

The digital image of the face of a person can be matched against a record of other images by using face recognition software. In case that some of the images in the database go with the digitized image, the owner is reported about it by the system. Automatic face recognition has been studied and investigated extensively since 1990s and its usage is turning out to be no-nonsense in the present times. Although a number of automatic face recognition applications are relatively agreeable and harmless (access regulation to armaments, currency, illegal proof, nuclear equipment/supplies etc), there are still several dangers of face recognition systems that include violation of privacy and civil liberties, unrestrained exploitation, identity theft, illegal use of database, free access to personal data on social media etc. (Agre, 2001).

Shi Et al [13] used a local projection profile at each pixel of the image, and transform the original image into an adaptive local connectivity map (ALCM). For this process, first the gray scale image is reversed so the foreground pixels (text) have idensity values of up to 255. Then the image is downsample to ¼ of each size, ½ in each direction. Next a sliding window of size 2c scans the image from left to right, and right to left in order to compute the cumulative idensity of every neighborhood. This technique is identical to computing the projection profile of every sliding window, (i.e. counting the foreground pixels), but instead of outpiting a projection profile histogram, the entire sliding window sum is saved on the ALCM image. Finaly

One frame from each camera is pulled into the program and then rectified based on calibration of each camera. The calibration process takes in the camera calibration parameters of the cameras, the rotation, and translation of the second camera in relation to the first camera. After being rectified based on the calibration, a disparity map is created. A disparity map is an intensity map that shows the measurements of

Then, we define the surfaces that will use in the scenes, through selecting their materials, specifying the required features in the surfaces such as the degree of reflectivity, and applying the images. Finally, the scenes are composed and organized through put the objects in the right position, determine the camera angles, and other related effects. [5]

The effort for this report is guided for occlusion, tracking mechanism, camera shift and spacio-temporal. All these techniques can be implemented for different usages.

being attacked, encrypt it with a secret key to obtain an encrypted bit stream . For that AES encryption is used. After AES encryption, will embed at the fourth bit position of . Some related information about the mosaic image generation process into the mosaic image for use in the secret image recovery process are also embed at the last fourth bit position of . Such information, described as a bit stream I like M, includes the following data items: 1) encryption key; and 2) total length of before encryption. After all this process Target image with mosaic image, residual value and all information that required to recover original image are transmitted to receiver

With the use of PCA, It becomes easy to reduce the complexity in images’ group (Karamizadeh et al., 2013).

In accession to the binary images, the proposed method may be tested on discrete color images also. These type of

Images that include geometric shapes that are repetitive to become a new photograph. Page 251

to produce and utilize the information about the original position of each segment from the raw

It can then be realized that the convention of the recognition scene is employed

In this paper “Facebook platform policies” [6] This is very important for achieving the accurate one-to-one correspondences. Finally, integrate our graph matching way into a hierarchical correspondence matching framework. It use multiple models to deal with the large inter subject anatomical variations and gradually refine the correspondence matching results between the tentatively deformed model images and the underlying subject image.

Various methods of image registration exist. However, this paper will focus on only five of the available methods.

Haven't you generally thought about whether wide-point photographs are a probability? Well! There you go.. They positively are. Picture Stitching is a procedure in which photographs of a normal size are sewed together to frame a solitary wide-point picture. This is frequently alluded to as an all encompassing picture. All encompassing Images are assembled in different ways such as a flat picture, a vertical picture, a rectilinear picture, a round picture and a full casing picture. Despite the fact that catching the whole region in a solitary shot is troublesome, it is not outlandish. Real estate agents, Wildlife Photographers exploit the all encompassing picture to put forth their defense.

Using the precise transformation matrix, any 3D data can be accurately overlaid over the video frame. Additionally, any pixel on the video frame can be translated back to latitude, longitude, and elevation using the transformation matrix and the synthetic 3D environment.