Ahmed Swilem

Learn More
Chromaffin cells of bovine adrenal medulla release catecholamines in response to activation of nicotinic ACh receptors which open voltage-sensitive calcium channels. Catecholamine secretion by exocytosis requires an increase in cytosolic free calcium. The cells also possess muscarinic ACh receptors but muscarinic agents do not provoke catecholamine release.(More)
In this paper, a fast search algorithm for mean pyramids vector quantization by using Hadamard transform of the vector is proposed. The algorithm uses mean pyramids of the vectors and codewords after applying Hadamard transform and one elimination criterion based on deviation characteristic values in the Hadamard transform domain to eliminate unlikely(More)
Vector quantization is the process of encoding vector data as an index to a dictionary or codebook of representative vectors. One of the most serious problems for vector quantization is the high computational complexity involved in searching for the closest codeword through the codebook. Entropy-constrained vector quantization (ECVQ) codebook design based(More)
In this paper, we propose two fast encoding algorithms for vector quantization. The first algorithm uses three significant features of a vector, that is , the norm, its projection angle to a reference line and the mean, to reduce the search area and accelerate the search process. The second algorithm has feature of using a suitable hyperplane to partition(More)
This article presents a very simple and efficient algorithm for codeword search in the vector quantization encoding. This algorithm uses 2-pixel merging norm pyramid structure to speed up the closest codeword search process. The authors first derive a condition to eliminate unnecessary matching operations from the search procedure. Then, based on this(More)
In this paper a new simple efficient algorithm for image descriptor using variance covariance matrix and variance calculations is presented. Also an approach to use this descriptor for image recognition is described. The recognition proceeds by matching individual features to a database of features from known images using a fast nearest-neighbor algorithm.(More)
Compressing an image is a significant technique for the sake of saving a little more bandwidth or storage space. However, one of the main problems in vector quantization (VQ) is the high computational complexity of searching for the appropriate codeword in its codebook. To overcome this problem a fast search algorithm based on Tree-Hadamard Transform of the(More)
In this paper, we propose a fast codebook generation algorithm for entropy-constrained vector quantization (ECVQ). The algorithm uses the angular constraint and employs a suitable hyperplane to partition the codebook and image data in order to reduce the search area and accelerate the search process in the codebook design. This algorithm allows significant(More)