Computer graphics: principles and practice (2nd ed.)
Computer graphics: principles and practice (2nd ed.)
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Computer Vision
Adaptive Image Segmentation by Combining Photometric Invariant Region and Edge Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Piecewise Linear Image Coding Using Surface Triangulation and Geometric Compression
DCC '00 Proceedings of the Conference on Data Compression
Generalized Hough Transform Using Regions with Homogeneous Color
International Journal of Computer Vision
Linear color segmentation and its implementation
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
Figure-ground separation by cue integration
Neural Computation
An Efficient Hillclimbing-based Watershed Algorithm and its Prototype Hardware Architecture
Journal of Signal Processing Systems
Computer Methods and Programs in Biomedicine
A scheme for ship detection in inhomogeneous regions based on segmentation of SAR images
International Journal of Remote Sensing
Object density-based image segmentation and its applications in biomedical image analysis
Computer Methods and Programs in Biomedicine
Edge Detection by Adaptive Splitting
Journal of Scientific Computing
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Intelligent object extraction algorithm based on foreground/background classification
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Edge Detection by Adaptive Splitting II. The Three-Dimensional Case
Journal of Scientific Computing
Segmentation of color images using a linguistic 2-tuples model
Information Sciences: an International Journal
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The performance of the classic split-and-merge segmentation algorithm is severely hampered by its rigid split-and-merge processes, which are insensitive to the image semantics. The author proposes efficient algorithms and data structures to optimize the split-and-merge processes by piecewise least-square approximation of image intensity functions. This optimization aims at the unification of segment finding and edge detection. The optimized split-and-merge algorithm is shown to be adaptive to the image semantics and, hence, improves the segmentation validity of the previous algorithms. This algorithm also appears to work well on noisy sources. Since the optimization is done within the split-and-merge framework, the better segmentation performance is achieved at the same order of time complexity as the previous algorithms.