1. Introduction. - 1. 1. Computational Complexities in Vision. - 1. 2. Review of Multiprocessor Architectures. - 1. 2. Organization. - 2. Model of Computation. - 2. 1. Parallelism in IVSs. - 2. 2. Data Dependencies. - 2. 3. Features and Capabilities of Parallel Architectures for IVSs. - 2. 4. Examples of Integrated Vision Systems. - 3. Architecture of NETRA. - 3. 1. Processor Clusters. - 3. 2. The DSP Hierarchy. - 3. 3. Global Memory. - 3. 4. Global Interconnection. - 3. 5. IVS Computation Requirements and NETRA. - 3. 6. Comparison of NETRA with Other Architectures. - 4. Parallel Algorithms on a Cluster. - 4. 1. Classification of Common Vision Algorithms. - 4. 2. Issues in Mapping an Algorithm. - 4. 3. Performance Evaluation of Parallel Algorithms. - 4. 4. Parallel Implementation Results. - 4. 5. Summary. - 5. Inter-Cluster Communication In NETRA. - 5. 1. Alternatives for Inter-cluster Communication. - 5. 2. Analysis of Inter-cluster Communication. - 5. 3. Approach to Performance Evaluation. - 5. 4. Performance of Parallel Algorithms on Multiple Clusters. - 5. 5. Summary. - 6. Load Balancing and Scheduling Techniques. - 6. 1. Need for Efficient Load Balancing Techniques. - 6. 2. Load Balancing and Scheduling Techniques for Parallel Implementation. - 6. 3. Parallel Implementation and Performance Evaluation. - 7. Concluding Remarks. - 7. 1. Summary and Discussion. - 7. 2. Extensions. - References. Language: English