JAVA IMAGE PROCESSING

Compressed Video Steganography

ABSTRACT
Steganography is the art and science of writing hidden messages in such a way that no one apart from the intended recipient knows of the existence of the message. The word "Steganography" is of Greek origin and means "covered, or hidden writing".An encrypted file may still hide information using Steganography, so even if the encrypted file is deciphered, the hidden message is not seen. Steganography used in electronic communication include steganographic coding inside of a transport layer, such as an MP3 file, or a protocol, such as UDP. The advantage of steganography over cryptography alone is that messages do not attract attention to themselves, to messengers, or to recipients. A steganographic message (the plaintext) is often first encrypted by some traditional means, and then a hidden text is modified in some way to contain the encrypted message (cipher text), resulting in stego text.

             

Content Based Image Retrieval

ABSTRACT
Due to the rapidly growing amount of digital image data on the Internet and in digital libraries, there is a great need for large image database management and effective image retrieval tools. Content-based image retrieval (CBIR) is the set of tech¬niques for searching for similar images from an image database using automatically extracted image features. Tremendous research has been devoted to CBIR and a variety of solutions have been proposed within the past ten years. By and large, research activities in CBIR have progressed in three major directions: global features based, object/region-level features based, and relevance feedback. Initially, developed sys¬tems are usually based on the carefully selected global image features, such as color, texture or shapes, and prefixed similarity measure. They are easy to implement and perform well for images that are either simple or contain few semantic contents (for example, medical images and face images). How¬ever, for these systems, it is impossible to search for objects or regions of the image. Therefore, the second group of sys¬tems is proposed on image segmentation. Contrasting

             

Data Hiding in Image File Using Steganography

ABSTRACT
Steganography is the art and science of writing hidden messages in such a way that no-one apart from the sender and intended recipient even realizes there is a hidden message. By contrast, cryptography obscures the meaning of a message, but it does not conceal the fact that there is a message. Today, the term steganography includes the concealment of digital information within computer files.

             

Fuzzy Noise Reduction

ABSTRACT
A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of two stages. The first stage computes a fuzzy derivative for eight different directions. The second stage uses these fuzzy derivatives to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Both stages are based on fuzzy rules which make use of membership functions. The filter can be applied iteratively to effectively reduce heavy noise. In particular, the shape of the membership functions is adapted according to the remaining noise level after each iteration, making use of the distribution of the homogeneity in the image.Astatistical model for the noise distribution can be incorporated to relate the homogeneity to the adaptation scheme of the membership functions. Experimental results are obtained to show the feasibility of the proposed approach. These results are also compared to other filters by numerical measures and visual inspection.

             

Identification Of Subsequence Videos

ABSTRACT
This Project presents a graph transformation and matching approach to identify the occurrence of potentially different ordering or length due to content editing. With a novel batch query algorithm to retrieve similar frames, the mapping relationship between the query and database video is first represented by a bipartite graph. The densely matched parts along the long sequence are then extracted, followed by a filter-and-refine search strategy to prune some irrelevant subsequences. During the filtering stage, Maximum Size Matching is deployed for each sub graph constructed by the query and candidate subsequence to obtain a smaller set of candidates. During the refinement stage, Sub-Maximum Similarity Matching is devised to identify the subsequence with the highest aggregate scores from all candidates, according to a robust video similarity model that incorporates visual content, temporal order, and frame alignment information.

             

Image Compression

ABSTRACT
Image Compression is mainly used for compeering the image data with out any significant image data or image clarity. This is for easy maintenance, network transforming and security also provided. In this project the lossy compression techniques can be used in some contexts where data loss cannot affect the image clarity in this area. In some important situations image compression uses Lossless compression involves with compressing data which, when decompressed, will be an exact replica of the original data. This is the case when binary data such as executables, documents etc. are compressed. They need to be exactly reproduced when decompressed. On the other hand, images (and music too) need not be reproduced 'exactly'. An approximation of the original image is enough for most purposes, as long as the error between the original and the compressed image is tolerable.

             

Image Consequence Utility

ABSTRACT
It contains all the tools you need for creating, editing, and retouching your images. It is friendly enough for the casual user who wants to enhance family photographs, yet powerful enough for the professional who needs to work with Images containing maps or with Image Processing or Artificial Intelligence. The user may access the tools and Utilities both from Toolbars at the click of a mouse as well as through menus. To see the name of a tool button, place the cursor over it. A pop-up hint, referred to as a ToolTip, appears. Note also that Image Consequence Utility displays a short description of the feature in the Status bar, which is located along the bottom of the workspace. Several features have been added to the "Image Consequence Utility" that helps in efficient processing of all kinds of Images.

             

Image Enhancement Tech

ABSTRACT
The field of Digital Image Processing refers to processing digital images by means of digital computer. One of the main application areas in Digital Image Processing methods is to improve the pictorial information for human interpretation. Most of the digital images contain noise. This can be removed by many enhancement techniques. Filtering is one of the enhancement techniques which is used to remove unwanted information (noise) from the image. It is also used for image sharpening and smoothening.

             

Image Stream Transfer Using Real Time Transmission Protocol

ABSTRACT
The Image transport protocol for the internet is developed with the aim of reducing the pit fall of TCP in the case of sloe connections and avoiding time consuming in manual process .This process provides efficient transmission of image over a network with high success criteria.

             

J BAR Coder

ABSTRACT
The Basic purpose of this project is to generate barcode Library using Java application, by implementing different type of algorithm. It supports number of barcode formats and this application can be use and enhanced for whatever reason you like. These barcodes contain encoded authenticated information, which gives a unique identity to any product, and provide a security labels.

             

Masking Of Images

ABSTRACT
Hiding image in a color image is a very interesting research topic, especially using very popular software such as Microsoft Windows Paint, Internet Explorer Browser (IE) Mozilla Firefox, etc can achieve very amazing result. In this paper, we start from the select operation of IE, and introduce the mechanism how to hide a color image in a real natural image. Based on this, we generate an animation using this scheme. Using the select function of IE, we can toggle two completely different animations. We improve the hiding scheme and introduce how to embed the shares of visual cryptography into a natural color image, another share of visual cryptography works as a public key like the select operation of IE. We also introduce how to hide a visual cryptography share into a halftone image. The results are very robust and can resist print and scan tempering.

             

Script Recognition

ABSTRACT
Automatic identification of handwritten script facilitates many important applications such as automatic transcription of multilingual documents and search for documents on the web containing a particular script. The increase in the usage of handheld devices which accept handwritten input has created a growing demand for algorithms that can efficiently analyze and retrieve handwritten data. Online documents may be written in different languages and scripts. A single document page in itself may contain text written in multiple scripts.

             

Structure & Texture Filling

ABSTRACT
Generally images are most commonly compressed by lossy JPEG. JPEG divides the image into blocks of 8*8 pixels. In general scenarios, the image is transmitted over the wireless channel block by block. Due to severe fading, we may lose an entire block or even several consecutive blocks of an image. It is also reported that average packet loss rate is about 3.6% and occurs in a bursty fashion. In the worst case, a whole line of image blocks might be lost. Two common techniques to make the transmission robust are forward error correction (FEC) and automatic retransmission query protocols (ARQ). Of these, FEC needs extra error correction packets to be transmitted. ARQ lowers data transmission rates and can further increase the network congestion which initially induced the packet loss.