Enhanced Mottle Measurement

The characterization of mottle, both for unprinted substrates and printed material, is becoming an increasingly important metric to predict and measure the quality of hardcopy output. Currently there are three methods commonly in use: Visual examination and comparison to some standard samples; use of a camera or scanner and image processing software to evaluate mottle using a method based on the ISO/IEC 13660 standard algorithm; and quantitative analysis with a vision system that allows tailoring of the algorithm to separate the components of the mottle artifacts. Mottle is a defect that can certainly degrade the perception of the quality of a print. Perception is dependent on several factors, including spatial frequency (size), contrast, sharpness, and viewing conditions (including illumination and distance). Therefore, mottle should be characterized taking these factors into consideration. If elimination or minimization of mottle is desired in order to improve the quality of the end product, the detection of mottle is necessary but not sufficient. Quantitative analysis provides the data to identify components comprising the mottle, allowing causal relationships to be established. This paper will detail two methods of quantifying mottle. One uses variable high pass spatial filters to separate the frequency components of the variation in the uniformity. The other characterizes the actual non-uniformity as cluster­ type defects and allows quantification by size, contrast, and morphology. Introduction—Description of Mottle Mottle is usually defined as the blotchy variation in reflected intensity (or density) for nominally uniform printed or unprinted surfaces. There are several manifestations of such nonuniformities in the world of printed hardcopy output. They are all generally characterized as mottle, but are differentiated by their size. Several examples include graininess and granularity (usually smaller sized defects or high frequency variation), and mottle (defined as larger defects or lower frequency variation). Each has a different cause, so independent characterization and identification is required to provide detection and appropriate corrective action (process and quality control). For the remainder of this paper, the process of independent characterization will be referred to as separation of variables. Analyses of media and print quality are generally used for one of two purposes. The first is relative or comparative—such as those used for competitive benchmarking. For this purpose, all that is required is a quantitative metric that yields a relative number that can be scaled for overall quality and thresholded for acceptability. The comparative metric may or may not report the aggregate effects due to multiple causes. The second purpose is process or quality control. Here is it critical that any components of the defects be detected and characterized to determine (or verify) their cause to enable tracking and correction. In this case, absolute quantified results are required. Examples of each type of approach will be described in the following sections, along with a methodology that allows extraction of discrete quantifiable results from an integrated relative metric. Mottle Variables and HVR The objective characterization of mottle should correlate to the human observer’s capability to perceive such nonuniformity. There are two primary components to this phenomenon: size (spatial frequency) and contrast (difference from the integrated average intensity). The variable of contrast has two possible manifestations. The perceived defects can be either darker or lighter than the integrated average. As noted above, differences in size may be attributable to differences in cause. Likewise, differences in polarity are usually indicative of disparate sources of the problem. While instrumentation exists to characterize mottle to any resolution in both size and contrast, it serves no practical purpose to detect and eliminate mottle that is not perceptible by the human visual system. There are limits to the range of defect size detectable, defined in terms of spatial frequency. Since visual acuity is defined in terms of solid angle subtended, considering components in terms of spatial frequency allows broader relevance to applications designed for different viewing distances. However, the visual acuity relationship is affected by context. In other words, both the absolute intensity level and the contrast affect the limits of perceptibility. Therefore a complete characterization of mottle must be a matrix of both these variables, namely size and contrast.