Green vegetation segmentation in color images is a fundamental issue for automated remote sensing and machine vision applications, plant ecological assessments, precision crop management, and weed control. A simple green vegetation feature extraction method (GVFE) is proposed in this paper to segment the green vegetation from their non-green backgrounds due to the fact that the green component content is always greater than that of the red and blue in RGB color space. The conventional based-auto-threshold method, ExG (Excess Green) was compared with GVFE, in which a green index ratio was defined to evaluate the performance of them. A digital color image set of single Canna flower taken in natural lighting were used to test them. Experimental results have showed that GVFE has superior performance over ExG+auto-threshold in term of stability, and is insensible to illuminant variations.
A kind of shared multi-channel on-chip memory architecture (SMC-OCM) for embedded CMPs is proposed in this article. To implement SMC-OCM architecture, the sharable multi-channel on-chip memory (MC-OCM) is designed and implemented based on FPGA. The characteristic of multiple data channel of MC-OCM assures good parallel responsiveness of SMC-OCM system. Experiments showed that the access latency of SMC-OCM is lower than that of the-state-of arts. SMC-OCM architecture satisfies the performance requirements for memory system by embedded applications
As a formal modeling and analysis method, colored petri nets (CPN) fits to construct formal model for software/hardware system with lots of communication and parallel/synchronous sharing behavior. Then behavior analysis of system function and performance based on the CPN model can be unfolded to verify the system feasibility. The CPN model of a kind of new CMP architecture shared multi-channel L2 Cache (AUMCC) is constructed in this article. Processing simulating of instruction set is deeply penetrated on the AUMCC CPN model, and analysis based on simulating results well verifies the feasibility of AUMCC architecture.
A kind of shared multi-channel on-chip memory CMP architecture is proposed in this article to efficiently support embedded applications. For the multi-channel on-chip memory being scarce resource, optimal space management mechanism of multi-channel on-chip memory is proposed including automatic space allocation strategy based on application parallelization mapping pattern and optimal space utilization scheme. ILP-model-based analysis of system performance verifies that the proposed optimal space management mechanism can deeply exploit the efficiency of multi-channel on-chip memory to improve system performance.
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