EVALUATION TECHNIQUES

Evaluation Techniques



Evaluation Techniques

Performance evaluation is a key aspect of any research, and throughout this thesis the image derivative operators developed are evaluated with respect to their performance in edge detection. Numerous edge evaluation techniques are available for evaluating gradient operators with respect to various aspects of edge detection, such as location, orientation and connectivity, and those that are used for evaluation in this thesis are outlined in §2.9.1 - §2.9.4. Although it is not described here, the method of local edge coherence (Kitchen and Rosenfeld, 1981) was implemented, but as (Venkatesh and Rosin, 1995) found, the results for this technique simply generally improved as the threshold value applied increased, and hence as the edges were deleted.

This definition is hardly perfect. There are many types of evaluations that do not necessarily result in an assessment of worth or merit -- descriptive studies, implementation analyses, and formative evaluations, to name a few. Better perhaps is a definition that emphasizes the information-processing and feedback functions of evaluation. For instance, one might say:

Both definitions agree that evaluation is a systematic endeavor and both use the deliberately ambiguous term 'object' which could refer to a program, policy, technology, person, need, activity, and so on. The latter definition emphasizes acquiring and assessing information rather than assessing worth or merit because all evaluation work involves collecting and sifting through data, making judgements about the validity of the information and of inferences we derive from it, whether or not an assessment of worth or merit results.

The generic goal of most evaluations is to provide "useful feedback" to a variety of audiences including sponsors, donors, client-groups, administrators, staff, and other relevant constituencies. Most often, feedback is perceived as "useful" if it aids in decision-making. But the relationship between an evaluation and its impact is not a simple one -- studies that seem critical sometimes fail to influence short-term decisions, and studies that initially seem to have no influence can have a delayed impact when more congenial conditions arise. Despite this, there is broad consensus that the major goal of evaluation should be to influence decision-making or policy formulation through the provision of empirically-driven feedback.

'Evaluation strategies' means broad, overarching perspectives on evaluation. They encompass the most general groups or "camps" of evaluators; although, at its best, evaluation work borrows eclectically from the perspectives of all these camps. Four major groups of evaluation strategies are discussed here.

Scientific-experimental models are probably the most historically dominant evaluation strategies. Taking their values and methods from the sciences -- especially the social sciences -- they prioritize on the desirability of impartiality, accuracy, objectivity and the validity of the information generated. Included under scientific-experimental models would be: the tradition of experimental and quasi-experimental designs; objectives-based research that comes from education; econometrically-oriented perspectives including cost-effectiveness and cost-benefit analysis; and the recent articulation of theory-driven evaluation.

The second class of strategies are management-oriented systems models. Two of the most common of these are PERT, the Program Evaluation and Review Technique, and CPM, the Critical Path ...