Parallel and Reconfigurable Mesh Architecture for Low and Medium Level Image Processing Applications

被引:0
作者
Soukaina, Ihirri [1 ]
Ahmed, Errami [1 ]
Mohamed, Khaldoun [1 ]
机构
[1] Hassan II Univ, RTSE, ENSEM, Casablanca, Morocco
来源
ADVANCES IN UBIQUITOUS NETWORKING 2 | 2017年 / 397卷
关键词
RMC; Low and Mid-level operations; Parallel processing; Image processing; COMPUTER; ALGORITHM;
D O I
10.1007/978-981-10-1627-1_42
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Image processing and especially real time image processing is a very compute intensive task. Nowadays, with the high volume of data to be processed and the increasing size of images, the development of image processing architectures is very required, but most cases of architectures are mostly limited to one single task. This work introduces a parallel Reconfigurable Mesh architecture called RMC (Reconfigurable Mesh Computer) suitable for image processing applications. This architecture provides the flexibility of a programmable architecture and performance of a dedicated circuit, geared to the efficient parallel execution of low and medium level image processing operations. These processing operations derive abstractions from the image pixels so that it can help in further decision making about image. Before describing the proposed architecture, this paper reviews the criteria to be taken into consideration to compare image processing architecture, reinforced by an illustration of some hardware image processing architectures. We also identify some performed applications on RMC, to finally conclude with our future research directions for RMC architecture.
引用
收藏
页码:529 / 544
页数:16
相关论文
共 23 条
[1]   N-Dimensional Twin Torus Topology [J].
Andujar-Munoz, Francisco J. ;
Villar-Ortiz, Juan A. ;
Sanchez, Jose L. ;
Jose Alfaro, Francisco ;
Duato, Jose .
IEEE TRANSACTIONS ON COMPUTERS, 2015, 64 (10) :2847-2861
[2]  
[Anonymous], 2007, EFFICIENT LIST RANKI
[3]  
[Anonymous], 2014, SEGMENTATION IMAGES
[4]   A fast algorithm for k-Nearest Neighbor Problem on a reconfigurable mesh computer [J].
Bouattane, O ;
Elmesbahi, J ;
Khaldoun, M ;
Rami, A .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2001, 32 (03) :347-360
[5]  
Deguchi K., 1990, 10 INT C PATT REC P, V2, P442
[6]   θ(1) time algorithm for structural characterization of multi-leveled images and its applications on a reconfigurable mesh computer [J].
Errami, A ;
Khaldoun, M ;
Elmesbahi, J ;
Bouattane, O .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2005, 44 (04) :277-290
[7]  
Geisler W. S., 2001, EDGE COOCCURENCE NAT
[8]  
Hwang Jyh-Jing, 2015, Pixel-wise deep learning for contour detection
[9]   PIPE (PIPELINED IMAGE-PROCESSING ENGINE) [J].
KENT, EW ;
SHNEIER, MO ;
LUMIA, R .
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 1985, 2 (01) :50-78
[10]  
Kushner T., 1982, IEEE T COMPUT