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This paper presents SCoPE (systolic chain of processing elements), a first step towards the realization of a generic systolic array for support vector machine (SVM) object classification in embedded image and video applications. SCoPE provides efficient memory management, reduced complexity, and efficient data transfer mechanisms. The proposed architecture is generic and scalable, as the size of the chain, and the kernel module can be changed in a plug and play approach without affecting the overall system architecture. These advantages provide versatility, scalability and reduced complexity that make it ideal for embedded applications. Furthermore, the SCoPE architecture is intended to be used as a building block towards larger systolic systems for multi-input or multi-class classification. Simulation results indicate real-time performance, achieving face detection at ~33 frames per second on an FPGA prototype.