scription “embedded block coding with optimized truncation”. (EBCOT) which identifies some of the major contributions of the algorithm. The EBCOT algorithm is. One of the major parts of JPEG is EBCOT (embedded block coding with optimized truncation) algorithm, which is needed to encode all bitplanes of every . One of the major parts of JPEG is EBCOT (embedded block coding with optimized truncation) algorithm, which is needed to encode all.

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Then, the location and scale of the key points is fixed by the three-dimensional quadratic function. Circuits and Systems for Video Technology.

Efficient Bit-Plane Coding Scheme for EBCOT Algorithm in JPEG

Seroussi, A lowcomplexity modeling approach for embedded coding ofwavelet coeffcients, Proc. Experiments show it is an efficient phase unwrapping method which well overcome the defect of under-estimate slopes by least squares algorithm, and has higher accuracy and stability than other methods.

Therefore, a new phase unwrapping and weights choosing method based on local phase frequency estimate of topographic factors was presented. Decoding algorithms with strong practical value not only have good decoding performance, but also have the computation complexity as low as possible.

Weighted least squares phase unwrapping algorithm could avoid errors transmission in the whole phase images, but it could not avoid defect and overlay of interference fringes caused by topographic factors.

A Image Watermarking Resisting Geometrical Attacks Based on EBCOT Algorithm

Fingerprint image has been aligned by rotating through an angle before feature vector is computed and matched. For this purpose, the paper points out the modified min-sum decoding algorithm M-MSA. The proposed algorithm is computationally very efficient and can be implemented on Real-Time Systems. Then WSR watermarking survival rate is used to search for the optimized truncation points by running the EBCOT process, the truncation point is adjusted to stay at the bit plane boundary and it is used as the dividing point to split magnitude bits of wavelet coefficients, which is then sent to EBCOT for encoding.


The algorithm has been tested on the FVC Databases.

The phase of complex signals is wrapped since it can only be measured modulo-2; unwrapping searches for the 2-combinations that minimize the discontinuity of alforithm unwrapped phase, as only the unwrapped phase can be analyzed and interpreted by further processing. This paper presents a fast and reliable algorithm for fingerprint verification.

Fingerprint Matching Based on Orientation Feature. At a threshold level of 1.

High performance scalable image compression with EBCOT.

Prasad Yarlagadda and Yun-Hae Kim. The final output is the J2K coded watermarked image. In order to achieve high accuracy and robust performance, the pixel level candidate regions are firstly identified by Harris detector.

This paper presents a novel sub-pixel corner detection algorithm for camera calibration. Mechatronics and Industrial Informatics.

Ravinder Kumar, Pravin Chandra, M. Row and Column variance feature vector of orientation image will be employed. This paper, proposes a method that by generating a pseudo random pattern, which will work as the watermark and the watermark is embedded during the quantization procedure.

The results show that watermarked EBCOT image is nearly rate-distortion optimized, the decoder can recover the original image, the watermark can be detected effectively, and it is robust against geometric attacking such as rotating attack, cropping and scaling attack.


Wavelet tree quantization for copyright protection watermarking[J].

Instead of using the intensity value of the regions, we propose to use corner response function CRF as the distribution of the weights of COG. Applied Mechanics and Materials Volumes The improved orientation feature vector of two fingerprints has been compared to compute the similarities at a given threshold. Experimental results show that the algorithm has good stability in translation, rotation and affine transformation, especially with 10 percent normalized Gaussian noise, this algorithm can still be detected feature points accuracy.

On the condition of no increasing in the decoding complexity, it makes the error-correcting performance improved by adding the appropriate scaling factor based on the min-sum algorithm MSAand it is very suitable for hardware implementation.

Our proposed fingerprint verification algorithm is based on image-based fingerprint matching. Within these regions, the center of gravity COG method is used to gain sub-pixel corner detection.

The results of camera calibration experiments show that the proposed algorithm is more accurate and robust than traditional COG sub-pixel corner detection methods.

First of all, the scale transformation of original image is adopted by the Gaussian kernel to building the DOG multi-scale pyramid. Simulation results show that this algorithm has good BER performance, low complexity and low hardware resource utilization, and it would be well applied in the future.