R. Forchheimer and A. Astrom, "Near-sensor image processing: A new paradigm," IEEE Trans. Image Processing, vol. 3, pp. 736--746, Nov. 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... time an event is received [e.g. Traditionally, the intensity to time relationship has been used in single and double slope A D converters [10] In vision, it has been used to improve diffusion based image segmentation [7] a local operation, and for image acquisition in a SIMD architecture [9] an architecture well suited only for local operations. In contrast, our architecture allows global operations and shares some features of traditional MIMD parallel processing. Namely, the local processors perform their operations asynchronously, an essential feature for the quick response and ....

R. Forchheimer and A. Astrom, "Near-sensor image processing: A new paradigm," IEEE Trans. Image Processing, vol. 3, pp. 736--746, Nov. 1994.

....a photodiode is associated with an A D converter and a digital PE. A D conversion is performed by using multiple thresholds, successively applied on the output of the photodiode operated in the integrating mode. This allows grey level vision to be performed while only processing binary images [5]. The digital PE has five duties: data storage, in binary registers or local memory; data communication, within the PE or between neighbor PEs; boolean computations, including bit serial ones, to process images; I O communication, from the A D converter, to the outside of the SIMD ....

....of variables. This may lead to unacceptable execution time. This problem can be alleviated by using larger values of M, that allow to iteratively compose operators or to exploit more advanced representations of boolean functions. That is also necessary for sequence or grey level image processing [5]. Table 1 (cf. 4) shows the values chosen for the memory capacity M in different PARs. M2 M1 S S S S M2 M1 M2 M1 (a) b) Figure 2: a) Standard unidirectional (eastward) shift register, obtained by linking together semi static binary registers as the one shown on figure 3d (note that the ....

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R. Forchheimer and A. Astrom. Near-sensor image processing: A new paradigm. IEEE Transactions on Image Processing, 3(6):736746, November 1994.

....where data from the entire image is needed for the processing task (e.g. count the number of elements) Classification, that tells what we see. Near Sensor Image Processing (NSIP) is a method to integrate as many of these tasks as possible in a single chip. The NSIP concept is described in [1], 2] 3] and in section III.B. B. Circuit solution The circuitry is a Sensory Processing Element (SPE) formed by an image detector and a processor. The SPEs are connected in an matrix and perform image sensing and parallel signal processing. The SPEs have local connection to its neighbors and ....

R. Forchheimer and A. strm, "Near-Sensor Image Processing. A New Paradigm", IEEE Transaction on Image Processing, Vol. 3, no. 6, pp 736-746, November 1994.

....trigger at times determined by the magnitude of their input operands, the global processor serves only a few local processors at a time. The intensity to time relationship has been used to improve image segmentation [3] a local operation, and for image processing in a SIMD architecture [4]. In contrast, our architecture allows global operations and shares some features of traditional MIMD parallel processing. Namely, the local processors perform their operations asynchronously, an essential feature for a quick response and the low latency performance of parallel systems. 3 Sorting ....

Forchheimer R. and A. Astrom, "Near--Sensor Image Processing: A New Paradigm," IEEE Trans. on Image Proc., Vol. 3, No. 6, pp. 736--746, November 1994.

....trigger at times determined by the magnitude of their input operands, the global processor serves only a few local processors at a time. The intensity to time relationship has been used to improve image segmentation [3] a local operation, and for image processing in a SIMD architecture [4]. In contrast, our architecture allows global operations and shares some features of traditional MIMD parallel processing. Namely, the local processors perform their operations asynchronously, an essential feature for a quick response and the low latency performance of parallel systems. LOCAL ....

Forchheimer R. and A. Astrom, "Near--Sensor Image Processing: A New Paradigm," IEEE Trans. on Image Proc., Vol. 3, No. 6, pp. 736--746, November 1994.

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