Parallel Image Understanding on a Multi-DSP System

A course-grain multiprocessor architecture, based on an array of digital signal processors (DSPs), is presented to demonstrate the possibility of a parallel implementation of image-understanding algorithms. Aerial image understanding is investigated as an application. The system is designed to exploit temporal and spatial parallelism. A good speed-up was obtained for low-and intermediate-level operations. However, the speed-up for high-level operations was poor because of processor idle times, as the number of objects to be processed at higher level tends to be small. DSPs performed well as processing elements for number-crunching operations, but the performance was not so good for implementing symbolic operations.

[1]  Y. C. Hecker,et al.  On Geometric Hashing and the Generalized Hough Transform , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[2]  Emanuel Diamant.  Paving the Way for Image Understanding: A New Kind of Image Decomposition Is Desired , 2005, SCIA.

[3]  Mohamed S. Kamel,et al.  Image Analysis and Recognition , 2014, Lecture Notes in Computer Science.

[4]  Paul Robertson.  An Architecture for Self-Adaptation and Its Application to Aerial Image Understanding , 2000, IWSAS.

[5]  Takashi Matsuyama,et al.  SIGMA: A Knowledge-Based Aerial Image Understanding System , 1990 .

[6]  Marek R. Ogiela,et al.  Picture Languages in Medical Pattern Knowledge Representation and Understanding , 2005, MDAI.

[7]  Yu-Fai Fung,et al.  The design and evaluation of a multiprocessor system for computer vision , 2000, Microprocess. Microsystems.

[8]  Leszek Wojnar,et al.  Image Analysis , 1998 .

[9]  W. Eric L. Grimson.  Medical Applications of Image Understanding , 1995, IEEE Expert.

[10]  N. Ranganathan,et al.  Corner detection , 1990, Pattern Recognit..

[11]  Wei He,et al.  Image mining for investigative pathology using optimized feature extraction and data fusion , 2005, Comput. Methods Programs Biomed..

[12]  Albert Y. Zomaya.  Parallel and Distributed Computing Handbook , 1995 .

[13]  Panagiota Spyridonos,et al.  Integration of Expert Knowledge and Image Analysis Techniques for Medical Diagnosis , 2006, ICIAR.

[14]  K. Navulur.  Multispectral Image Analysis Using the Object-Oriented Paradigm , 2006 .

[15]  Jean-François Delaigle,et al.  Real-time high-level video understanding using data warehouse , 2006, Electronic Imaging.

[16]  Larry S. Davis,et al.  Foundations of Image Understanding , 2001 .

[17]  Luca Lombardi,et al.  Hierarchical architectures for computer vision , 1995, Proceedings Euromicro Workshop on Parallel and Distributed Processing.

[18]  Fangju Wang,et al.  A knowledge-based vision system for detecting land changes at urban fringes , 1993, IEEE Trans. Geosci. Remote. Sens..