Digital Signal Processing

Contains an introduction and reports on fifteen research projects.U.S. Navy - Office of Naval Research (Contract N00O14-81-K-0742)U.S. Navy - Office of Naval Research (Contract N00014-77-C-0266)National Science Foundation (Grant ECS80-07102)National Science Foundation (Grant ECS84-07285)Amoco Foundation FellowshipSanders Associates, Inc.Advanced Television Research ProgramM.I.T. Vinton Hayes FellowshipHertz Foundation Fellowshi

Digital Signal Processing

Contains an introduction and reports on fourteen research projects.National Science Foundation FellowshipNational Science Foundation (Grant ECS84-07285)U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)Sanders Associates, Inc.U.S. Air Force - Office of Scientific Research (Contract F19628-85-K-0028)Advanced Television Research ProgramAmoco Foundation FellowshipHertz Foundation Fellowshi

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Contains the table of contents

Biometrics in Cyber Security

Computers play an important role in our daily lives and its usage has grown manifolds today. With ever increasing demand of security regulations all over the world and large number of services provided using the internet in day to day life, the assurance of security associated with such services has become a crucial issue. Biometrics is a key to the future of data/cyber security. This paper presents a biometric recognition system which can be embedded in any system involving access control, e-commerce, online banking, computer login etc. to enhance the security. Fingerprint is an old and mature technology which has been used in this work as biometric trait. In this paper a fingerprint recognition system based on no minutiae features: Fuzzy features and Invariant moment features has been developed. Fingerprint images from FVC2002 are used for experimentation. The images are enhanced for improving the quality and a region of interest (ROI) is cropped around the core point. Two sets of features are extracted from ROI and support vector machine (SVM) is used for verification. An accuracy of 95 per cent is achieved with the invariant moment features using RBF kernel in SVM

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Mengenal pasti tahap pengetahuan pelajar tahun akhir Ijazah Sarjana Muda Kejuruteraan di KUiTTHO dalam bidang keusahawanan dari aspek pengurusan modal

Malaysia ialah sebuah negara membangun di dunia. Dalam proses pembangunan ini, hasrat negara untuk melahirkan bakal usahawan beijaya tidak boleh dipandang ringan. Oleh itu, pengetahuan dalam bidang keusahawanan perlu diberi perhatian dengan sewajarnya; antara aspek utama dalam keusahawanan ialah modal. Pengurusan modal yang tidak cekap menjadi punca utama kegagalan usahawan. Menyedari hakikat ini, kajian berkaitan Pengurusan Modal dijalankan ke atas 100 orang pelajar Tahun Akhir Kejuruteraan di KUiTTHO. Sampel ini dipilih kerana pelajar-pelajar ini akan menempuhi alam pekeijaan di mana mereka boleh memilih keusahawanan sebagai satu keijaya. Walau pun mereka bukanlah pelajar dari jurusan perniagaan, namun mereka mempunyai kemahiran dalam mereka cipta produk yang boleh dikomersialkan. Hasil dapatan kajian membuktikan bahawa pelajar-pelajar ini berminat dalam bidang keusahawanan namun masih kurang pengetahuan tentang pengurusan modal terutamanya dalam menentukan modal permulaan, pengurusan modal keija dan caracara menentukan pembiayaan kewangan menggunakan kaedah jualan harian. Oleh itu, satu garis panduan Pengurusan Modal dibina untuk memberi pendedahan kepada mereka

Curvelet Transform based Retinal Image Analysis

Edge detection is an important assignment in image processing, as it is used as a primary tool for pattern  recognition, image segmentation and scene analysis.  An edge detector is a high-pass filter that can be applied for extracting the edge points within an image. Edge detection in the spatial domain is  accomplished through convolution with a set of directional derivative masks in this domain. On the other hand, working in the  frequency domain has many advantages, starting from introducing an alternative description to the  spatial representation and providing more efficient and faster computational schemes with less sensitivity  to noise through high filtering, de-noising and compression algorithms. Fourier transforms, wavelet and  curvelet transform are among the most widely used frequency-domain edge detection from satellite  images. However, the Fourier transform is global and poorly adapted to local singularities. Some of  these draw backs are solved by the wavelet transforms especially for singularities detection and  computation. In this paper, the relatively new multi-resolution technique, curvelet transform, is assessed  and introduced to overcome the wavelet transform limitation in directionality and scaling.  In this research paper, the assessment of second generation curvelet transforms as an edge detection tool  will be introduced and compared with first generation cuevelet transform.DOI:http://dx.doi.org/10.11591/ijece.v3i3.245