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image segmentation mini projects using matlab


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Created at: Friday 01st of February 2013 01:27:12 PM
Last Edited Or Replied at :Saturday 02nd of February 2013 02:28:45 AM
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please kindly a..................[:=> Show Contents <=:]



Medical image segmentation using clustering algorithm


Posted by: computer science technology
Created at: Friday 29th of January 2010 08:12:36 PM
Last Edited Or Replied at :Thursday 08th of November 2012 01:30:40 AM
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hed segmentation algorithm to it. The kmeans clustering is an unsupervised learning algorithm, while the improved watershed segmentation algorithm makes use of automated thresholding on the gradient magnitude map and post-segmentation merging on the initial partitions to reduce the number of false edges and over-segmentation. By comparing the number of partitions in the segmentation maps of 50 images, we showed that our proposed methodology produced segmentation maps which have 92% fewer partitions than the segmentation maps produced by the conventional watershed algorithm
Technology Used : ..................[:=> Show Contents <=:]



SPEECH RECOGNITION USING DSP full report


Posted by: computer science technology
Created at: Sunday 24th of January 2010 10:22:35 AM
Last Edited Or Replied at :Monday 16th of January 2012 12:34:38 AM
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ation areas such as control access to services like voice dialing, banking by telephone, database access services, voice mail, security control for confidential information areas, and remote access to computers.


Principles of Speaker Recognition
Speaker recognition can be classified into identification and verification. Speaker identification is the process of determining which registered speaker provides a given utterance. Speaker verification, on the other hand, is the process of accepting or rejecting the identity claim of a speaker. Figure 1 shows the basic structures..................[:=> Show Contents <=:]



Edge detection of textured images


Posted by: electronics seminars
Created at: Saturday 16th of January 2010 12:41:45 PM
Last Edited Or Replied at :Saturday 16th of January 2010 12:41:45 PM
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texture; this configuration varies rapidly with distance slowly in coarse textures. An occurrence of some grey level configuration may be described by a matrix of relative frequencies P,d (a, b) describing how frequently two pixels with the grey level a, b appear in the window separated by a distance d in the direction .
2.2 Textural Feature Extraction
The filtering approaches to texture classification generally compute the filter output statistics as features. Figure 1 describes a typical scheme of textural feature extraction. The textured image is filtered through a bank of filters ..................[:=> Show Contents <=:]



java based projects


Posted by: electronics seminars
Created at: Friday 15th of January 2010 12:42:03 PM
Last Edited Or Replied at :Thursday 28th of January 2010 06:14:17 AM
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em
q. Right protection for catero logical data..................[:=> Show Contents <=:]



Image Processing for Edge Detection


Posted by: electronics seminars
Created at: Tuesday 12th of January 2010 08:27:06 PM
Last Edited Or Replied at :Tuesday 12th of January 2010 08:27:06 PM
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e between different pixels. The edge-detection operator is calculated by forming a matrix centered on a pixel chosen as the center of the matrix area. If the value of this matrix area is above a given threshold, then the middle pixel is classified as an edge. Examples of gradient-based edge detectors are Roberts, Prewitt, and Sobel operators. All the gradient-based algorithms have kernel operators that calculate the strength of the slope in directions, which are orthogonal to each other, commonly vertical and horizontal. Later, the contributions of the different components of the slopes are co..................[:=> Show Contents <=:]



image processing projects


Posted by: electronics seminars
Created at: Monday 04th of January 2010 05:49:06 AM
Last Edited Or Replied at :Saturday 21st of April 2012 11:34:33 AM
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LOR IMAGES
c. IMPLEMENTATION OF EDGE DETECTION TECHNIQUES USING MATLAB
d. IMPLEMENTATION OF SPATIAL AND FREQUENCY DOMAIN TECHNIQUES FOR IMAGE ENHANCEMENT
e. IMPLEMENTATION OF HISTOGRAM EQUALIZATION TECHNIQUES
f. IMAGE COMPRESSION USING BIORTHOGONAL 3.7 WAVELET TRANSFORMS
g. IMPLEMENTAION OF IMAGE RESTORATION & IMAGE ENHANCEMENT TECHNIQUES USING MATLAB
h. IMPLEMENTATION OF ALGORITHMS FOR SUCCESSIVE INTERFERENCE CANCELLATION IN CDMA USING MATLAB
i. IMPLEMENTATION OF WCDMA USING VHDL
j. IMAGE WATERMARKING USING WAVELETS & DIRECTIONAL FILTER BANKS
k. MORPHOLOGICAL OPERATORS FOR COLOR IMA..................[:=> Show Contents <=:]



Image Processing


Posted by: computer science crazy
Created at: Monday 22nd of September 2008 12:04:19 AM
Last Edited Or Replied at :Monday 22nd of September 2008 12:04:19 AM
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ery user friendly.

Medical equipments like Ultra Sound, CT etc? have images at their output in the AVI file format, which are acquired with the respective probes. These AVI images acquired are stored. The software captures this AVI image, displays them frame-by-frame in succession and converts them to DICOM image with required patient's details obtained from the Specialist during conversion. The frame of interest can be freezed and converted to Bitmap image, which can also be viewed on a separate window with options to brighten, darken, change the color combination, invert the image and re..................[:=> Show Contents <=:]



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