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An approach for the computer-assisted analysis of two-dimensional gels has been developed as a part of our laboratory information processing system (LIPS). This approach relies in part on an algorithm for the pairwise matching of protein spots. The matching process initially matches spots based on a cross-correlational measure of how well neighboring spots align. While this first pass correctly determines most spot correspondences and noncorrespondences, it can make errors. Higher accuracy is obtained by monitoring the consistency of spot match decisions in a second pass, which demands that neighboring spot pairs that align spatially must also have been found to match in the first pass. Pairwise comparisons of gels are combined into n-way comparisons by matching spot lists of gels to "master" gel spot lists, which in turn are matched to higher level masters, resulting in a hierarchy of matched spots. After each pairwise match the results are reviewed and corrected with the assistance of a graphical match-editor. Results are given for 19 single-cell-derived lymphoid clones in which the presence of a mutation had previously been established, each processed in duplicate. Only one of 46 spot changes failed to be detected, which demonstrates that the strategy is sensitive and efficient for detecting qualitative spot differences.

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The applicability of morphological image processing techniques for the description of condition and analysis of pavement surfaces is examined. Morphological techniques can be used in the measurement of pavement media consisting of grain (aggregates) and binding substances (bituminous or Portland cement mixtures). Measurements of size and size distributions on surface features related to texture and distresses can be obtained via morphological opening and closing transformations and distributions. When correlated with actual physical measurements of such quantities, the presented morphological measures of size and size distributions may prove to be useful in characterizing the surface condition of both asphalt and concrete pavement structures. INTRODUCTIONMathematical morphology (Serra, 1982) is a theory of image analysis which has its roots in applications involving the properties of materials, e.g., metalurgy ) and geology . The present study represents an initial effort to apply morphological operations in processing images of pavement surfaces, with the goal of relating various morphological measures to the analysis and characterization of the condition of pavement structures. SCOPE OF PRESENT RESEARCH The GoalThe broad goal of the present research is to develop an automated roadway condition data acquisition and analysis system. This goal is pursued in an effort towards the concurrent development of two distinct component systems, namely: (a) a surface vision system for roadway surface condition detection and image analysis, and (b) a condition evaluation system for the interpretation of the measurements derived from image processing and their correlation to physical parameters descriptive of the roadway surface condition.loads; (c) skid resistance, which measures the frictional capacity of a pavement surface ABSTRACT The applicability of morphological image processing techniques for the description of condition and analysis of pavement surfaces is examined. Morphological techniques can be used in the measurement of pavement media consisting of grain (aggregates) and binding substances (bituminous or Portland cement mixtures). Measurements of size and size distributions on surface features related to texture and distresses can be obtained via morphological opening and closing transformations and distributions. When correlated with actual physical measurements of such quantities, the presented morphological measures of size and size distributions may prove to be useful in characterizing the surface condition of both asphalt and concrete pavement structures.

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