Color Image Indexing Using Binay Truncation Coding
IEEE Transactions on Image Processing, Vol. 12, No. 1, January 2003
Language: Java, VB.NET
Project modules:
• Image File I/O
• Image Block Features Extraction
• Block Co-occurrence Analysis
• Image Classification
• Results and Analysis
Abstract:
This paper presents a new application of a well studied image coding technique, namely block truncation coding (BTC). It is shown that BTC can not only be used for compressing color images, it can also be conven ....etc

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Presented By
V. RAJITHA P.KAUMUDI


ABSTRACT:
In this paper, we propose a simple and efficient technique for embedded color image coding. The proposed algorithm exploits inter- and intra-sub band correlations of the wavelet transformed luminance (Y) and chrominance (U and V) planes as well a ....etc

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please send the documentation and source code ....etc

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Fast and Cheap Color Image Segmentation for Interactive Robots


Introduction
An important first step in many color vision tasks is to classify
each pixel in an image into one of a discrete number
of color classes. The leading approaches to accomplishing
this task include linear color thresholding, nearest neighbor
classification, color space thresholdingand probabilistic
methods.

Description of the Approach Color Space Transformation

Our appr ....etc

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This paper presents a zero tree coding method for color images that uses no lists during encoding and decoding,permitting the omission of the lists requirement in Said and Pearlman's Set Partitioning In Hierarchical Trees (SPIHT) algorithm . Without the lists, the memory requirement in a VLSI implementation is reduced significantly. This coding algorithm is also developed to reduce the circuit complexity of an implementation. Our experimental results show only a minor reduction of PSNR values when compared with the PSNR values obtained by th ....etc

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Query by Image Content
Using Shape & Color Characteristics
Introduction
Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases.
Content-based means that the search will analyze the actual contents of the image. The term 'content' in this context might refer colors, shapes, textures, o ....etc

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CBIR - Content Based Image Retrieval Using Shape & Color Characteristics
Introduction
Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases.
Content-based means that the search will analyze the actual contents of the image. The term 'content' in this context might refer colors, shapes, textur ....etc

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Fuzzy Random Impulse Noise Removal
From Color Image Sequences



Abstract

In this paper, a new fuzzy filter for the removal of
random impulse noise in color video is presented. By working with
different successive filtering steps, a very good tradeoff between
detail preservation and noise removal is obtained. One strong filtering
step that should remove all noise at once would inevitably
also remove a considerable amount of detail. Therefore, the noise
is filtered step by step. In each step, noisy pixe ....etc

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Towards Optimal Color Image Coding using Demosaicing
Abstract—We introduce an optimal approach to color image compression using demosaicing. Accordingly, we propose an efficient algorithm for color image coding. In the encoder, a
mosaic of the primary colors is encoded instead of the full color image. This mosaic is considered as four different color channels that are compressed using subband transform coders. In the decoder, a demosaicing algorithm is applied to the decompressed channels to reconstruct the ....etc

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Fast Multi-Resolution Image Querying Using Color Characteristics
Introduction
Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases.
Content-based means that the search will analyze the actual contents of the image. The term 'content' in this context might refer colors, shapes, textures, or ....etc

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